CN116415743B - Fruit and vegetable distribution optimization method based on-line dispatching system - Google Patents

Fruit and vegetable distribution optimization method based on-line dispatching system Download PDF

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CN116415743B
CN116415743B CN202310687353.2A CN202310687353A CN116415743B CN 116415743 B CN116415743 B CN 116415743B CN 202310687353 A CN202310687353 A CN 202310687353A CN 116415743 B CN116415743 B CN 116415743B
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vegetables
fruit
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CN116415743A (en
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孙炜
熊浩敏
周婷
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Shenzhen Agricultural Products Co ltd
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Abstract

The invention relates to the technical field of agricultural product path planning, and discloses a fruit and vegetable distribution optimization method based on an on-line dispatching system, which comprises the following steps: receiving a fruit and vegetable distribution optimizing instruction, determining an optimal distribution path according to the fruit and vegetable distribution optimizing instruction, acquiring the current storage amount of a distribution destination point by utilizing an on-line scheduling system, wherein the current storage amount is determined by stored fruits and vegetables in the distribution destination point, acquiring the maximum storage amount of the distribution destination point and the fruit and vegetable distribution amount of the fruits and vegetables to be distributed, when the fruits and vegetables to be distributed start to be distributed based on the optimal distribution path, executing dynamic warehouse-out on the stored fruits and vegetables based on the maximum storage amount and the current storage amount until the addition value of the current storage amount and the fruit and vegetable distribution amount is smaller than the maximum storage amount, completing dynamic warehouse-out and obtaining an idle position point for storing the fruits and vegetables to be distributed, and thus completing the distribution optimization of agricultural products. The invention can save the computing resource and solve the problem that the delivery destination stores excessive agricultural products.

Description

Fruit and vegetable distribution optimization method based on-line dispatching system
Technical Field
The invention relates to a fruit and vegetable distribution optimization method and device based on an on-line dispatching system, and belongs to the technical field of agricultural product path planning.
Background
With the continuous development of science and technology, the full supply chain intelligence degree based on agricultural products is popularized, wherein the agricultural product distribution optimization is a core link of the agricultural product supply chain. The agricultural product delivery optimization is a path planning process for transferring agricultural products from a planting point to a destination point according to the delivery requirements of users.
The conventional agricultural product distribution optimization is mainly based on particle swarm algorithm, fish swarm algorithm and the like, and the distribution optimization based on the particle swarm algorithm and the fish swarm algorithm can effectively complete user demands, but the quantity of agricultural product distribution demands is greatly improved, and each time of responding to an agricultural product distribution instruction, the particle swarm algorithm, the fish swarm algorithm and the like are excessively relied on to perform multiple iterative selection of an optimal path, so that the problem of excessive waste of calculation resources is caused. In addition, most of the agricultural product distribution optimization at present does not consider the contradiction problem between the agricultural product to be distributed and the stored agricultural product at the destination point, namely, the storage influence of the stored agricultural product at the destination point is not considered, so that the problem that excessive agricultural product is stored at the destination point, and the agricultural product is accumulated and rotten is often caused.
Disclosure of Invention
The invention provides a fruit and vegetable distribution optimization method and device based on an online dispatching system and a computer readable storage medium, and mainly aims to save calculation resources required by agricultural product distribution optimization, and solve the problems that excessive agricultural products are stored at a distribution destination and accumulation and decay of the agricultural products are accelerated.
In order to achieve the above purpose, the invention provides a fruit and vegetable distribution optimization method based on an on-line dispatching system, which comprises the following steps:
receiving a fruit and vegetable distribution optimizing instruction, determining fruits and vegetables to be distributed according to the fruit and vegetable distribution optimizing instruction, and storing refrigeration points of the fruits and vegetables to be distributed to obtain a first refrigeration point;
when fruits and vegetables to be distributed are transferred from a planting point to a first refrigerating point, an on-line dispatching system is utilized to receive picking data of the fruits and vegetables to be distributed, wherein the picking data comprise picking temperature of the fruits and vegetables to be distributed, picked from the planting point, and first transfer time of the fruits and vegetables to be distributed, transferred from the planting point to the first refrigerating point;
determining an initial quantitative value of the quality of the fruits and vegetables to be distributed according to the first transfer time and the picking temperature;
analyzing a fruit and vegetable distribution optimizing instruction to obtain distribution destination points, and determining a plurality of distribution paths between the first refrigeration points and the distribution destination points, wherein the distribution paths consist of the first refrigeration points, the second refrigeration points, the ith refrigeration point of …, the mth refrigeration point and the distribution destination points, the distribution starting point of each distribution path is the first refrigeration point, the distribution end point is the distribution destination point, i is more than or equal to 1, and m is the total number of the refrigeration points included in the distribution paths;
Obtaining distribution data of each distribution path, wherein the distribution data is obtained according to a first refrigeration point, a second refrigeration point, a … ith refrigeration point, an mth refrigeration point and a distribution destination point, and a distribution path selection function is constructed according to the distribution data and a quality initial quantization value;
solving each distribution path selection function to obtain a corresponding quality attenuation quantized value, selecting a minimum quantized value from all quality attenuation quantized values larger than zero, and determining a distribution path corresponding to the minimum quantized value as an optimal distribution path;
determining a client of a delivery destination point to obtain a delivery point client, connecting the delivery point client by using an online dispatching system, and obtaining the current storage quantity of the delivery destination point by using the delivery point client after the online dispatching system is successfully connected with the delivery point client, wherein the current storage quantity is determined by fruits and vegetables stored in the delivery destination point;
obtaining the maximum storage amount of a delivery destination point and the fruit and vegetable amount of fruits and vegetables to be delivered to obtain the fruit and vegetable delivery amount, when the fruits and vegetables to be delivered start to be delivered based on the optimal delivery path, based on the maximum storage amount and the current storage amount, performing dynamic delivery on stored fruits and vegetables until the addition value of the current storage amount and the fruit and vegetable delivery amount is smaller than the maximum storage amount, completing dynamic delivery and obtaining an idle position point for storing the fruits and vegetables to be delivered;
And sending the idle position points to an online dispatching system, and notifying a transport system for transporting fruits and vegetables to be distributed by using the online dispatching system, so that the distribution optimization of agricultural products is completed.
Optionally, the determining the initial quantitative value of the quality of the fruits and vegetables to be delivered according to the first transfer time and the picking temperature includes:
mapping and normalizing the first transfer time and the picking temperature to obtain normalized first transfer time and picking temperature;
calculating to obtain an initial quantitative value of the quality of the fruits and vegetables to be distributed according to the following formula:
wherein ,q0 An initial quantized value representing the quality of the fruit and vegetable to be dispensed,representing quality standard quantized values of fruits and vegetables to be dispensed, alpha represents weight factors of a calculation formula of quality initial quantized values, T 0 Representing the normalized picking temperature, t 0 Indicating the normalized first transfer time.
Optionally, the acquiring the delivery data of each delivery path includes:
sequentially acquiring historical delivery time from a first refrigeration point to a second refrigeration point, …, an i-1 refrigeration point to an i refrigeration point, …, an m refrigeration point and a delivery destination point from a historical database in an online dispatching system;
calculating average delivery time from the first refrigeration point to the second refrigeration point, …, from the i-1 refrigeration point to the i refrigeration point, …, from the m refrigeration point and the delivery destination according to the historical delivery time, and obtaining first delivery time, …, i delivery time, … and m delivery time;
Determining the time when the fruits and vegetables to be dispensed leave the first refrigeration point to obtain the dispensing start time, and respectively predicting the dispensing time periods from the first refrigeration point to the second refrigeration point, …, from the i-1 refrigeration point to the i refrigeration point, …, from the m refrigeration point and from the dispensing destination point based on the dispensing start time and the total length of the dispensing path to obtain a first time period, …, an i time period, … and an m time period;
starting a weather temperature system bound with the online dispatching system, and respectively predicting average temperatures of a first time period, …, an i-th time period, … and an m-th time period by using the weather temperature system to obtain a first average temperature, …, an i-th average temperature, … and an m-th average temperature;
and summarizing the first delivery time, …, the ith delivery time, … and the mth delivery time, and the first average temperature, …, the ith average temperature, … and the mth average temperature to obtain delivery data of each delivery path.
Optionally, the constructing a distribution path selection function according to the distribution data and the quality initial quantization value includes:
mapping and normalizing the distribution data to obtain normalized distribution data;
and constructing the following distribution path selection function by using the normalized distribution data and the quality initial quantized value:
wherein ,f(ti ,T i ) Represent the delivery path selection function, q m Representing the quantized value of the mass attenuation obtained by calculating the distribution path selection function, t i Representing the delivery time from the ith refrigeration point to the (i+1) th refrigeration point after normalization, namely the ith delivery time after normalization, T i Represents the average temperature from the ith refrigeration point to the (i+1) th refrigeration point after normalization, namely the ith average temperature after normalization, beta i At t i Fluctuation factor of G i Is T i And beta i And G i The values of (2) are all greater than zero and less than or equal to 1, and beta i And G i The generation rule of (2) accords with a normal function.
Optionally, the performing dynamic delivery of the stored fruits and vegetables further includes:
judging the addition value of the fruit and vegetable distribution amount and the current storage amount, and the size relation of the addition value and the maximum storage amount;
if the sum of the fruit and vegetable delivery amount and the current storage amount is smaller than or equal to the maximum storage amount, the stored fruit and vegetable does not need to be dynamically delivered out of the warehouse, and a delivery destination point is obtained and used for storing idle position points of the fruit and vegetable to be delivered;
when the idle position points are successfully obtained, directly distributing fruits and vegetables to be distributed to the idle position points;
and if the sum of the fruit and vegetable delivery quantity and the current storage quantity is larger than the maximum storage quantity, when the fruit and vegetable to be delivered starts to be delivered based on the optimal delivery path, the stored fruit and vegetable is dynamically delivered.
Optionally, when the fruit and vegetable to be delivered starts to be delivered based on the optimal delivery path, based on the maximum storage amount and the current storage amount, performing dynamic delivery of the stored fruit and vegetable, including:
when the fruits and vegetables to be distributed start to be distributed based on the optimal distribution path, acquiring the distribution starting time;
when the delivery starting time is successfully obtained, determining a delivery position point of the stored fruits and vegetables, and calculating to obtain the damage rate of the fruits and vegetables for conveying the stored fruits and vegetables to the delivery position point;
presetting a delivery starting time and a delivery speed for starting to execute delivery of stored fruits and vegetables, and constructing a dynamic delivery optimization model of the delivery starting time and the delivery speed based on the fruit and vegetable damage rate;
constructing a dynamic ex-warehouse constraint function of a dynamic ex-warehouse optimization model based on the maximum storage amount and the current storage amount;
on the premise of a dynamic ex-warehouse constraint function, solving a dynamic ex-warehouse optimization model to obtain an optimal value of ex-warehouse starting time and an optimal value of ex-warehouse speed;
and after the time reaches the optimal value of the delivery start time, performing dynamic delivery of the stored fruits and vegetables on the basis of the optimal value of the delivery speed.
Optionally, the constructing the dynamic delivery optimization model of the delivery start time and the delivery speed based on the fruit and vegetable damage rate includes:
Calculating the time when the fruits and vegetables to be delivered reach the delivery destination point, and obtaining the delivery destination time;
based on the ex-warehouse end time and the ex-warehouse start time, a dynamic ex-warehouse optimization model is constructed, wherein the dynamic ex-warehouse optimization model is as follows:
wherein ,indicating the start time of delivery of the stored fruits and vegetables at the delivery destination point>Indicating the delivery end time of the fruit and vegetable to be delivered to the delivery destination point,/day>The method comprises the steps of representing a quality loss quantized value of stored fruits and vegetables reaching a delivery position point from a delivery destination point, wherein gamma represents a fruit and vegetable damage rate of the stored fruits and vegetables, W (t) represents delivery quantity of the stored fruits and vegetables delivered from the delivery destination point at a time t, v (t) represents delivery speed of the stored fruits and vegetables delivered from the delivery destination point at the time t, oc represents positive correlation, mu is a weight factor of the fruit and vegetable damage rate, mu is greater than or equal to 1, and is in positive correlation with v (t), and mu is greater when v (t) is greater.
Optionally, the dynamic ex-warehouse constraint function is composed of a first ex-warehouse constraint function, a second ex-warehouse constraint function and a third ex-warehouse constraint function, where the first ex-warehouse constraint function is:
s.t.W c +W m ≥W k
wherein ,Wc Representing the current storage quantity, W m Representing the fruit and vegetable distribution amount, W k Indicating the delivery destination pointMaximum storage volume.
Optionally, the constructing of the second ex-warehouse constraint function includes:
calculating the distance between the delivery destination point and the delivery position point to obtain delivery length;
calculating the time to the warehouse end point of the stored fruits and vegetables reaching the warehouse-out position point based on the warehouse-out length and the warehouse-out speed, wherein the calculation method of the time to the warehouse end point is as follows:
wherein ,indicating the time to the end of the warehouse of the stored fruit and vegetable to the point of the delivery site, < >>Indicating the start time of delivery of the stored fruits and vegetables at the delivery destination point>Represents the average speed of delivery calculated from v (t), l c Representing a library length;
constructing a second ex-warehouse constraint function according to the time to the warehouse end point and the time to the ex-warehouse end point, wherein the second ex-warehouse constraint function is as follows:
wherein ,the delivery start time at which the delivery of the fruit and vegetable to be delivered is started is indicated.
Optionally, the third ex-warehouse constraint function is:
s.t.W c ≤W a ,W m ≤W a +W k -W c
wherein ,Wa Is shown inTo->And (3) total delivery of the stored fruits and vegetables from the delivery destination point to the delivery position point in the time period.
In order to solve the above-mentioned problems, the present invention also provides an electronic apparatus including:
At least one processor; the method comprises the steps of,
a memory communicatively coupled to the at least one processor; wherein,
the memory stores instructions executable by the at least one processor to implement the above-described fruit and vegetable distribution optimization method based on the on-line scheduling system.
In order to solve the above problems, the present invention further provides a computer readable storage medium, where at least one instruction is stored, where the at least one instruction is executed by a processor in an electronic device to implement the above-mentioned fruit and vegetable distribution optimization method based on an on-line scheduling system.
Compared with the prior art, the method comprises the steps of firstly receiving the fruit and vegetable distribution optimizing instruction, determining fruits and vegetables to be distributed according to the fruit and vegetable distribution optimizing instruction, and storing the refrigerating point of the fruits and vegetables to be distributed to obtain the first refrigerating point, and when the fruits and vegetables to be distributed are transferred from the planting point to the first refrigerating point, receiving picking data of the fruits and vegetables to be distributed by utilizing the on-line dispatching system, wherein the picking data comprise picking temperature of the fruits and vegetables to be distributed picked from the planting point and first transfer time of the fruits and vegetables to be distributed transferred from the planting point to the first refrigerating point, and the on-line dispatching system is the pivot of the method. Further, analyzing a fruit and vegetable distribution optimization instruction to obtain a distribution destination point, determining a plurality of distribution paths between a first refrigeration point and the distribution destination point, wherein the distribution paths consist of the first refrigeration point, a second refrigeration point, a … ith refrigeration point, an mth refrigeration point and the distribution destination point, the distribution starting point of each distribution path is the first refrigeration point, the distribution end point is the distribution destination point, i is 1 or more, m is the total number of refrigeration points included in the distribution paths, and distribution data of each distribution path are obtained according to the first refrigeration point, the second refrigeration point, the … ith refrigeration point, the mth refrigeration point and the distribution destination point, a distribution path selection function is constructed according to the distribution data and the quality initial quantization value, each distribution path selection function is solved, the corresponding quality attenuation quantization value is obtained, the minimum quantization value is selected from all the quality attenuation quantization values which are larger than zero, the distribution paths corresponding to the minimum quantization value are determined to be optimal distribution paths, and the distribution paths are calculated according to the distribution points, and the distribution data of the distribution paths are calculated according to the first refrigeration point, the second refrigeration point, the mth refrigeration point and the distribution destination point, the distribution path is further calculated according to the distribution data 35, and the distribution data of the distribution path selection nodes are calculated. In addition, after the path selection is completed, the client of the delivery destination point is determined to obtain the delivery point client, the on-line dispatching system is used for connecting the delivery point client, and after the on-line dispatching system is successfully connected with the delivery point client, the current storage amount of the delivery destination point is obtained by using the delivery point client, the maximum storage amount of the delivery destination point and the fruit and vegetable amount of the fruits and vegetables to be delivered are obtained, when the delivery of the fruits and vegetables to be delivered is started based on the optimal delivery path, based on the maximum storage amount and the current storage amount, the stored fruits and vegetables are dynamically delivered until the sum of the current storage amount and the fruit and vegetable delivery amount is smaller than the maximum storage amount, the dynamic delivery is completed and an idle position point for storing the fruits and vegetables to be delivered is obtained. Finally, the idle position points are sent to an online dispatching system, and the online dispatching system is used for informing a transport system for transporting fruits and vegetables to be distributed, so that the distribution optimization of agricultural products is completed. Therefore, the fruit and vegetable distribution optimization method based on the on-line scheduling system can save the calculation resources required by agricultural product distribution optimization, and solve the problems that excessive agricultural products are stored at a distribution destination and the accumulation and decay of the agricultural products are accelerated.
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Fig. 1 is a schematic flow chart of a fruit and vegetable distribution optimization method based on an on-line dispatching system according to an embodiment of the present application;
fig. 2 is a schematic structural diagram of an electronic device for implementing the fruit and vegetable distribution optimization method based on the on-line dispatching system according to an embodiment of the present application.
The achievement of the objects, functional features and advantages of the present application will be further described with reference to the accompanying drawings, in conjunction with the embodiments.
Detailed Description
It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the application.
The embodiment of the application provides a fruit and vegetable distribution optimization method based on an on-line dispatching system. The execution main body of the fruit and vegetable distribution optimization method based on the online dispatching system comprises at least one of electronic equipment which can be configured to execute the method provided by the embodiment of the application, such as a server side, a terminal and the like. In other words, the fruit and vegetable distribution optimization method based on the on-line dispatching system can be executed by software or hardware installed in the terminal equipment or the server equipment. The service end includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, and the like.
Example 1:
referring to fig. 1, a flow chart of a fruit and vegetable distribution optimization method based on an on-line dispatching system according to an embodiment of the present invention is shown. In this embodiment, the fruit and vegetable distribution optimization method based on the on-line scheduling system includes:
s1, receiving a fruit and vegetable distribution optimizing instruction, determining fruits and vegetables to be distributed according to the fruit and vegetable distribution optimizing instruction, and storing refrigeration points of the fruits and vegetables to be distributed to obtain a first refrigeration point.
It should be explained that the fruit and vegetable distribution optimization instruction is generally initiated or automatically triggered by a planter at a planting point, for example, 1000 jin of ripe grapes are collected in a planting point of a certain 1000 mu of grapes and are planned to be transported to a distribution destination point, and when 1000 jin of grapes are successfully placed into a refrigerating point near the planting point of the grapes from the planting point of the 1000 mu of grapes, the fruit and vegetable distribution optimization instruction is automatically triggered, so that a path from a first refrigerating point to a subsequent distribution destination point is intelligently planned.
S2, when the fruits and vegetables to be distributed are transferred to the first refrigeration point from the planting point, the on-line dispatching system is utilized to receive picking data of the fruits and vegetables to be distributed, wherein the picking data comprise picking temperatures of the fruits and vegetables to be distributed, picked from the planting point, and first transfer time of the fruits and vegetables to be distributed, transferred to the first refrigeration point from the planting point.
The on-line dispatching system is a full-flow follow-up and optimizing system for picking fruits and vegetables in a planting point, storing the fruits and vegetables and distributing the fruits and vegetables until the fruits and vegetables reach a distribution destination point, and has multiple functions. The embodiment of the invention discloses an intelligent planning function for optimizing a delivery path from fruit and vegetable picking by utilizing an on-line dispatching system.
By way of example, all grapes at a certain 1000 mu grape planting point are mature in midsummer, and how to intelligently transport the grapes at the planting point to different delivery destination points based on picking data of each grape and delivery data of subsequent delivery paths, so that the problems of grape quality degradation and even necrosis caused by path selection and the like and resource waste caused directly are solved.
Further, the picking data includes a picking temperature at which the fruit and vegetable is picked from the planting point and a first transfer time at which the fruit and vegetable is transferred from the planting point to the first refrigeration point. For example, if a planter with 1000 mu grape planting points is planted, the grape planting points of 1000 mu are ripe, so that 1000 jin of ripe grapes are collected on the same day, the corresponding picking temperature is 25 degrees through a sensor, after 1000 jin of grapes are collected, 1 hour is taken from the planting point to the first refrigeration point, and the 1 hour is the first transfer time.
S3, determining an initial quantitative value of the quality of the fruits and vegetables to be distributed according to the first transfer time and the picking temperature.
It should be understood that the collection temperature and the first transfer time affect the quality of the fruits and vegetables, that is, the higher the collection temperature and the longer the first transfer time, the worse the initial quality of the fruits and vegetables entering the first refrigeration point, but in order to facilitate the subsequent determination of the distribution methods of different fruits and vegetables according to different qualities of the fruits and vegetables, the embodiment of the invention needs to determine the initial quantitative value of the quality of the fruits and vegetables according to the first transfer time and the picking temperature.
In detail, the determining the initial quantitative value of the quality of the fruits and vegetables to be distributed according to the first transfer time and the picking temperature includes:
mapping and normalizing the first transfer time and the picking temperature to obtain normalized first transfer time and picking temperature;
calculating to obtain an initial quantitative value of the quality of the fruits and vegetables to be distributed according to the following formula:
wherein ,q0 An initial quantized value representing the quality of the fruit and vegetable to be dispensed,representing quality standard quantized values of fruits and vegetables to be dispensed, alpha represents weight factors of a calculation formula of quality initial quantized values, T 0 Representing the normalized picking temperature, t 0 Indicating the normalized first transfer time.
It should be explained that the main purpose of the mapping and normalization operation is to map the first transfer time and the picking temperature to the interval of [0,1], so as to prevent the mass calculation imbalance phenomenon caused by the excessive values of the first transfer time and the picking temperature. The mapping and normalization operations have more selectable methods, and are disclosed techniques, and the embodiments of the present invention are not described herein.
According to the above formula, the quality of fruits and vegetables can be quantified according to the picking environment where the fruits and vegetables are located and the transfer time of the fruit trees from the planting point to the storage point, so that the subsequent path planning is convenient.
S4, analyzing a fruit and vegetable distribution optimization instruction to obtain distribution destination points, and determining a plurality of distribution paths between the first refrigeration points and the distribution destination points, wherein the distribution paths consist of the first refrigeration points, the second refrigeration points, the … ith refrigeration points, the mth refrigeration points and the distribution destination points, the distribution starting point of each distribution path is the first refrigeration point, the distribution end point is the distribution destination point, i is more than or equal to 1, and m is the total number of the refrigeration points included in the distribution paths.
For example, 1000 jin of the grapes collected by the small sheets are intended to be sent to the large supermarket in the next-door market, the large supermarket in the next-door market is the distribution destination point, and the first refrigerating point where the small sheets are located reaches the large supermarket in the adjacent-door market and has 3 distribution paths, wherein the first distribution path is the first refrigerating point directly reaching the supermarket in the adjacent-door market, i.e. the first distribution path consists of the first refrigerating point and the supermarket in the adjacent-door market, the second distribution path consists of the first refrigerating point, the second refrigerating point and the supermarket in the adjacent-door market, and the third distribution path consists of the first refrigerating point, the second refrigerating point, the third refrigerating point and the supermarket in the adjacent-door market.
And S5, obtaining the distribution data of each distribution path, wherein the distribution data is obtained according to the first refrigerating point, the second refrigerating point, the ith refrigerating point of …, the mth refrigerating point and the distribution destination point, and the distribution path selection function is constructed and obtained according to the distribution data and the quality initial quantized value.
In detail, the acquiring the delivery data of each delivery path includes:
sequentially acquiring historical delivery time from a first refrigeration point to a second refrigeration point, …, an i-1 refrigeration point to an i refrigeration point, …, an m refrigeration point and a delivery destination point from a historical database in an online dispatching system;
calculating average delivery time from the first refrigeration point to the second refrigeration point, …, from the i-1 refrigeration point to the i refrigeration point, …, from the m refrigeration point and the delivery destination according to the historical delivery time, and obtaining first delivery time, …, i delivery time, … and m delivery time;
determining the time when the fruits and vegetables to be dispensed leave the first refrigeration point to obtain the dispensing start time, and respectively predicting the dispensing time periods from the first refrigeration point to the second refrigeration point, …, from the i-1 refrigeration point to the i refrigeration point, …, from the m refrigeration point and from the dispensing destination point based on the dispensing start time and the total length of the dispensing path to obtain a first time period, …, an i time period, … and an m time period;
Starting a weather temperature system bound with the online dispatching system, and respectively predicting average temperatures of a first time period, …, an i-th time period, … and an m-th time period by using the weather temperature system to obtain a first average temperature, …, an i-th average temperature, … and an m-th average temperature;
and summarizing the first delivery time, …, the ith delivery time, … and the mth delivery time, and the first average temperature, …, the ith average temperature, … and the mth average temperature to obtain delivery data of each delivery path.
It should be explained that the quality of the fruits and vegetables to be delivered is mainly affected by the delivery paths, for example, the delivery time is too long, the temperature of the delivery process is too high or too low due to the too long delivery paths, and the quality of the fruits and vegetables to be delivered can be directly affected.
The second distribution path is formed by a first refrigeration point, a second refrigeration point and a supermarket in the vicinity of the market, and all historical data about the first refrigeration point to the second refrigeration point and the second refrigeration point to the supermarket in the vicinity of the market in the second distribution path are obtained in the online dispatching system, wherein the average time required by the first refrigeration point to the second refrigeration point is calculated according to the historical data in sequence, and the average time is the first distribution time. Further, assuming that 1000 jin of grapes leave the first refrigeration point and are 5 in the morning at 2023, 5 month and 29, and the first refrigeration point and the second refrigeration point are close in distance, the corresponding first time period is 2023, 5 in the morning at 29, 5 in the morning and 8 in the morning, so that the average temperature from 5 in the morning at 29 in the 5 months to 8 in the morning is 19 degrees through a weather temperature system, and the 19 degrees are the first average temperature.
It should also be noted that the first, …, i-th, …, and m-th time periods are typically not continuous. As the first time period from 5 a in the morning to 8 a in the 29 th year of 2023, the second time period is not necessarily from 8 a in the morning, and the phenomenon that the second time period starts from 5 a in the afternoon may occur, so as to put the grapes waiting for dispensing fruits and vegetables at the second refrigeration point to perform refrigeration, so as to prevent the quality of the fruits and vegetables to be dispensed from being affected due to too high temperature when dispensing is performed in the high-temperature weather in the noon.
Further, the constructing and obtaining a distribution path selection function according to the distribution data and the quality initial quantization value includes:
mapping and normalizing the distribution data to obtain normalized distribution data;
and constructing the following distribution path selection function by using the normalized distribution data and the quality initial quantized value:
wherein ,f(ti ,T i ) Represent the delivery path selection function, q m Representing the quantized value of the mass attenuation obtained by calculating the distribution path selection function, t i Representing the delivery time from the ith refrigeration point to the (i+1) th refrigeration point after normalization, namely the ith delivery time after normalization, T i Represents the average temperature from the ith refrigeration point to the (i+1) th refrigeration point after normalization, namely the ith average temperature after normalization, beta i At t i Fluctuation factor of G i Is T i And beta i And G i The values of (2) are all greater than zero and less than or equal to 1, and beta i And G i The generation rule of (2) accords with a normal function.
It should be explained that, the fluctuation factor is also called random disturbance factor, because the calculation of the mass attenuation quantized value is an ideal condition, but a plurality of unpredictable factors often appear in the actual scene, so that the main effect of the fluctuation factor is to simulate the unpredictable factors appearing in the actual scene, thereby achieving the effect of more accurate calculation of the mass attenuation quantized value.
And S6, solving each distribution path selection function to obtain a corresponding quality attenuation quantized value, selecting a minimum quantized value from all quality attenuation quantized values larger than zero, and determining a distribution path corresponding to the minimum quantized value as an optimal distribution path.
It can be understood that according to the distribution path selection function, the quality attenuation quantized value of the fruit and vegetable to be distributed under each distribution path can be calculated in sequence, so that the distribution path corresponding to the smallest quality attenuation quantized value is selected, namely the optimal distribution path. For example, the 1000 jin of grapes are intended to be sent to a large supermarket in a next-door market, and a total of 3 distribution paths are calculated to obtain a minimum mass attenuation quantized value of a second distribution path (consisting of a first refrigeration point, a second refrigeration point and a supermarket in the adjacent market), so that the second distribution path is selected as an optimal distribution path.
And S7, determining a client of the delivery destination point to obtain the client of the delivery point, connecting the client of the delivery point by using an online dispatching system, and obtaining the current storage quantity of the delivery destination point by using the client of the delivery point after the online dispatching system is successfully connected with the client of the delivery point, wherein the current storage quantity is determined by fruits and vegetables stored in the delivery destination point.
For example, if the distribution destination point of 1000 jin of grapes is a large supermarket in a parterre, the client for managing the storage of the supermarket is determined to be the distribution point client. It should be explained that, the delivery point client records the number of fruits and vegetables to be delivered stored in the delivery destination point at the current time in real time, so that the current storage amount of the delivery destination point can be obtained from the delivery point client after the delivery point client is successfully connected through the online dispatching system. Assuming that the storage amount of the grapes in the supermarket in the adjacent market is 5000 jin, and the supermarket can only store 5500 jin of grapes at most, the 1000 jin of grapes cannot meet the storage requirement after being sent, and therefore 5000 jin of stored grapes need to be processed.
S8, obtaining the maximum storage amount of the delivery destination point and the fruit and vegetable amount of the fruits and vegetables to be delivered to obtain the fruit and vegetable delivery amount, when the fruits and vegetables to be delivered start to be delivered based on the optimal delivery path, based on the maximum storage amount and the current storage amount, performing dynamic delivery of the stored fruits and vegetables until the sum of the current storage amount and the fruit and vegetable delivery amount is smaller than the maximum storage amount, completing dynamic delivery and obtaining an idle position point for storing the fruits and vegetables to be delivered.
It can be understood that 1000 jin of grapes are fruit and vegetable distribution quantities, and the supermarket can only store 5500 jin of grapes at most, so that 5500 jin of grapes are maximum storage quantities, and the current storage quantity of the grapes in the market in the adjacent supermarket is 5000 jin, so that 5000 jin is the current storage quantity.
Further, the performing dynamic delivery of the stored fruits and vegetables includes:
judging the addition value of the fruit and vegetable distribution amount and the current storage amount, and the size relation of the addition value and the maximum storage amount;
if the sum of the fruit and vegetable delivery amount and the current storage amount is smaller than or equal to the maximum storage amount, the stored fruit and vegetable does not need to be dynamically delivered out of the warehouse, and a delivery destination point is obtained and used for storing idle position points of the fruit and vegetable to be delivered;
when the idle position points are successfully obtained, directly distributing fruits and vegetables to be distributed to the idle position points;
and if the sum of the fruit and vegetable delivery quantity and the current storage quantity is larger than the maximum storage quantity, when the fruit and vegetable to be delivered starts to be delivered based on the optimal delivery path, the stored fruit and vegetable is dynamically delivered.
It can be understood that when the sum of the fruit and vegetable delivery amount and the current storage amount is less than or equal to the maximum storage amount, the delivery destination point still has a space for accommodating the fruit and vegetable to be delivered, so that in order to save the computing resources of the on-line dispatching system, the delivery can be directly started without executing dynamic delivery. In addition, it should be explained that when the application scenario of the agricultural product involves dynamic planning, the place where the delivery destination point is used for storing the agricultural product is very huge in general, and in order to prevent mutual infection, tamper and the like between the agricultural products, the delivery destination point is generally divided into a plurality of storage compartments, and the storage compartments are isolated from each other, so in the embodiment of the invention, the idle position point is generally assigned with the position information of the storage compartment and the number of the storage compartment in the point of delivery, and the position information and the number of the storage compartment are obtained in advance, so that the transportation system for transporting the fruits and vegetables to be delivered can be helped to transport the fruits and vegetables to be delivered to the delivery destination point faster, and the problem of agricultural product waste caused by that the specific storage information of the fruits and the vegetables to be delivered cannot be obtained after reaching the delivery destination point is prevented.
In addition, it should be emphasized that the conventional agricultural product distribution optimization scheme generally only involves the problem of path optimization in the distribution process, and the coordination relationship between the storage capacity and the distribution capacity of the storage point is rarely considered. Because most agricultural products belong to perishable goods and are required to be refrigerated at low temperature so as to ensure freshness, in the embodiment of the invention, when the sum of the fruit and vegetable delivery amount and the current storage amount is larger than the maximum storage amount, stored fruits and vegetables in the delivery destination point are not cleaned immediately, but dynamic delivery is started when the fruits and vegetables to be delivered start delivery, so that the dynamic coordination process between the fruits and vegetables to be delivered and the stored fruits and vegetables is ensured, and the problem that the quality of the stored fruits and vegetables is reduced too quickly due to early delivery of the fruits and vegetables is avoided as much as possible while the storage of the fruits and vegetables to be delivered is not influenced.
Further, when the fruit and vegetable to be delivered starts to be delivered based on the optimal delivery path, based on the maximum storage amount and the current storage amount, the method for dynamically delivering the stored fruit and vegetable includes:
when the fruits and vegetables to be distributed start to be distributed based on the optimal distribution path, acquiring the distribution starting time;
when the delivery starting time is successfully obtained, determining a delivery position point of the stored fruits and vegetables, and calculating to obtain the damage rate of the fruits and vegetables for conveying the stored fruits and vegetables to the delivery position point;
Presetting a delivery starting time and a delivery speed for starting to execute delivery of stored fruits and vegetables, and constructing a dynamic delivery optimization model of the delivery starting time and the delivery speed based on the fruit and vegetable damage rate;
constructing a dynamic ex-warehouse constraint function of a dynamic ex-warehouse optimization model based on the maximum storage amount and the current storage amount;
on the premise of a dynamic ex-warehouse constraint function, solving a dynamic ex-warehouse optimization model to obtain an optimal value of ex-warehouse starting time and an optimal value of ex-warehouse speed;
and after the time reaches the optimal value of the delivery start time, performing dynamic delivery of the stored fruits and vegetables on the basis of the optimal value of the delivery speed.
Illustratively, the time for 1000 jin of grapes to leave the first cold storage point is 2023, 5 months 29 a.m. 5 a, and 2023, 5 months 29 a.m. 5 a is the dispensing start time. In the embodiment of the invention, when the delivery start time is successfully obtained, the delivery position point of the stored fruits and vegetables is determined, and in general, the delivery position point can be a point of sale or the next storage point. For example, the current storage amount of the grapes in a supermarket in the vicinity of the supermarket is 5000 jin, and 800 jin of stored grapes are planned to be distributed into the point of sale of another supermarket cooperated with the supermarket, and the point of the warehouse-out position is the point of sale of the other supermarket.
It can be understood that, between the delivery position point and the delivery destination point, the quality of the stored fruits and vegetables is lost due to the reasons of distance length, temperature change, transportation collision and the like. In the embodiment of the invention, parameters such as the distance between the delivery position point and the delivery destination point, the temperature change of delivery at the moment, the stored time of the stored fruits and vegetables at the delivery destination point and the like can be used as input parameters of a fruit and vegetable damage rate prediction model, so that the fruit and vegetable damage rates of different stored fruits and vegetables can be predicted, wherein the fruit and vegetable damage rate prediction model can adopt models such as a support vector machine and Xgboost.
It should be explained that, the stored fruits and vegetables are stored in the delivery destination point for too long, so that compared with the fruits and vegetables to be delivered which are just picked from the planting point, the fruits and vegetables are more strict in delivery conditions, so that a dynamic delivery optimization model needs to be constructed, and the optimal delivery starting time and delivery speed are solved.
Further, the dynamic delivery optimization model for constructing delivery starting time and delivery speed based on the fruit and vegetable damage rate comprises the following steps:
calculating the time when the fruits and vegetables to be delivered reach the delivery destination point, and obtaining the delivery destination time;
based on the ex-warehouse end time and the ex-warehouse start time, a dynamic ex-warehouse optimization model is constructed, wherein the dynamic ex-warehouse optimization model is as follows:
/>
wherein ,indicating the start time of delivery of the stored fruits and vegetables at the delivery destination point>Indicating the delivery end time of the fruit and vegetable to be delivered to the delivery destination point,/day>The method comprises the steps of representing a quality loss quantized value of stored fruits and vegetables reaching a delivery position point from a delivery destination point, wherein gamma represents a fruit and vegetable damage rate of the stored fruits and vegetables, W (t) represents delivery quantity of the stored fruits and vegetables delivered from the delivery destination point at a time t, v (t) represents delivery speed of the stored fruits and vegetables delivered from the delivery destination point at the time t, oc represents positive correlation, mu is a weight factor of the fruit and vegetable damage rate, mu is greater than or equal to 1, and is in positive correlation with v (t), and mu is greater when v (t) is greater.
The method and the device are characterized in that the delivery speed represents the delivery speed of the process of delivering the stored fruits and vegetables from the delivery destination point to the delivery position point, and it is understood that the longer the stored fruits and vegetables are stored at the delivery destination point, the greater the probability that the stored fruits and vegetables are damaged during transportation is, and therefore, the smaller the delivery speed is, the smaller the collision probability of the stored fruits and vegetables during transportation is, and the lower the damage rate of the stored fruits and vegetables is, so that the embodiment of the invention constructs a positive correlation relation between the delivery speed and the damage rate of the fruits and vegetables, wherein the calculation function adopted by the positive correlation relation comprises, but is not limited to, one-time functions and other increasing functions.
Further, the dynamic ex-warehouse constraint function is composed of a first ex-warehouse constraint function, a second ex-warehouse constraint function and a third ex-warehouse constraint function, wherein the first ex-warehouse constraint function is as follows:
s.t.W c +W m ≥W k
wherein ,Wc Representing the current storage quantity, W m Representing the fruit and vegetable distribution amount, W k Indicating the maximum storage amount of the delivery destination point.
In addition, the constructing of the second ex-warehouse constraint function includes:
calculating the distance between the delivery destination point and the delivery position point to obtain delivery length;
calculating the time to the warehouse end point of the stored fruits and vegetables reaching the warehouse-out position point based on the warehouse-out length and the warehouse-out speed, wherein the calculation method of the time to the warehouse end point is as follows:
wherein ,indicating the time to the end of the warehouse of the stored fruit and vegetable to the point of the delivery site, < >>Indicating the start time of delivery of the stored fruits and vegetables at the delivery destination point>Represents the average speed of delivery calculated from v (t), l c Representing a library length;
constructing a second ex-warehouse constraint function according to the time to the warehouse end point and the time to the ex-warehouse end point, wherein the second ex-warehouse constraint function is as follows:
wherein ,the delivery start time at which the delivery of the fruit and vegetable to be delivered is started is indicated.
It should be explained that, in the embodiment of the present invention, the time when the stored fruits and vegetables reach the delivery destination point (the time when the stored fruits and vegetables reach the delivery destination point) should not exceed the time when the fruits and vegetables to be delivered reach the delivery destination point (the time when the stored fruits and vegetables reach the delivery destination point), while the conventional time constraint function is constructed, the time when the stored fruits and vegetables leave the delivery destination point should be set earlier than the time when the fruits and vegetables to be delivered reach the delivery destination point, which is practically feasible in principle, but does not meet the actual scene requirement.
Further, the third ex-warehouse constraint function is:
s.t.W c ≤W a ,W m ≤W a +W k -W c
wherein ,Wa Is shown inTo->And (3) total delivery of the stored fruits and vegetables from the delivery destination point to the delivery position point in the time period.
It can be understood that according to the three groups of the delivery constraint functions, the optimal delivery start time and delivery speed in the dynamic delivery optimization model can be calculated, so that further, after the time reaches the optimal value of the delivery start time, the stored fruits and vegetables are dynamically delivered based on the optimal value of the delivery speed until the delivery of the stored fruits and vegetables is completed, and the idle position point for storing the fruits and vegetables to be delivered is obtained.
And S9, sending the idle position points to an online dispatching system, and notifying a transport system for transporting fruits and vegetables to be distributed by using the online dispatching system, so that the distribution optimization of agricultural products is completed.
As can be seen from the above description S8, the space for storing the dispensing destination point of agricultural products is very large, and the dispensing destination point is required to be divided into a plurality of storage compartments for preventing the agricultural products from being infected and tampered with, and in many cases, the storage compartments are isolated from each other, and the entrance of the storage compartment is quite different from the entrance of the storage compartment, and the storage compartment a may enter from the north door of the dispensing destination point, and the storage compartment B may enter from the south door of the dispensing destination point, so the free location point generally assigns the location information of the storage compartment and the number of the storage compartment in the dispensing destination point, and the location information and the number of the storage compartment are obtained in advance, which can help the transportation system for transporting the fruits and vegetables to be dispensed to the dispensing destination point more quickly, and prevent the quality of the agricultural products from being affected due to the fact that the specific information of the storage compartment for the fruits and vegetables to be dispensed cannot be obtained after the dispensing destination point is reached.
Therefore, the embodiment of the invention sends the idle position points positioned in the delivery destination points to the on-line dispatching system, the on-line dispatching system is used as a junction system, and the idle position points are sent to the transport system for transporting the fruits and vegetables to be delivered again, so that the transport system knows how to reach the idle position points more quickly after reaching the delivery destination points, and the quality loss of agricultural products in the transportation process is avoided to the lowest extent, thereby completing the delivery optimization of the agricultural products.
Compared with the problems in the prior art, the embodiment of the invention firstly receives the fruit and vegetable distribution optimizing instruction, determines the fruit and vegetable to be distributed according to the fruit and vegetable distribution optimizing instruction, and is used for storing the refrigerating point of the fruit and vegetable to be distributed to obtain the first refrigerating point, and when the fruit and vegetable to be distributed is transferred from the planting point to the first refrigerating point, the on-line dispatching system is utilized to receive picking data of the fruit and vegetable to be distributed, wherein the picking data comprises the picking temperature of the fruit and vegetable to be distributed picked from the planting point and the first transfer time of the fruit and vegetable to be distributed transferred from the planting point to the first refrigerating point. Further, analyzing a fruit and vegetable distribution optimization instruction to obtain a distribution destination point, determining a plurality of distribution paths between a first refrigeration point and the distribution destination point, wherein the distribution paths consist of the first refrigeration point, a second refrigeration point, a … ith refrigeration point, an mth refrigeration point and the distribution destination point, the distribution starting point of each distribution path is the first refrigeration point, the distribution end point is the distribution destination point, i is 1 or more, m is the total number of refrigeration points included in the distribution paths, and the distribution data of each distribution path is obtained, wherein the distribution data is obtained according to the first refrigeration point, the second refrigeration point, the … ith refrigeration point, the mth refrigeration point and the distribution destination point, a distribution path selection function is constructed according to the distribution data and the quality initial quantization value, each distribution path selection function is solved, the corresponding quality attenuation quantization value is obtained, the minimum quantization value is selected from all the quality attenuation quantization values which are larger than zero, the distribution paths corresponding to the minimum quantization value are determined to be optimal distribution paths, and in order to improve the distribution path selection resolution ratio, the distribution paths are calculated as the first refrigeration point, the second refrigeration point, the mth refrigeration point and the distribution destination point is calculated, the distribution path is further saved, and the distribution path is calculated according to the distribution point 35, and the distribution path is further convenient to construct. In addition, after the path selection is completed, the client of the delivery destination point is determined to obtain the delivery point client, the on-line dispatching system is used for connecting the delivery point client, and after the on-line dispatching system is successfully connected with the delivery point client, the current storage amount of the delivery destination point is obtained by using the delivery point client, the maximum storage amount of the delivery destination point and the fruit and vegetable amount of the fruits and vegetables to be delivered are obtained, when the fruits and vegetables to be delivered start to be delivered based on the optimal delivery path, the stored fruits and vegetables are subjected to dynamic delivery based on the maximum storage amount and the current storage amount, until the sum of the current storage amount and the fruit and vegetable delivery amount is smaller than the maximum storage amount, the dynamic delivery is completed and the idle position point for storing the fruits and vegetables to be delivered is obtained. Finally, the embodiment of the invention sends the idle position points to an online dispatching system, and the online dispatching system is used for notifying a transport system for transporting fruits and vegetables to be distributed, so that the distribution optimization of agricultural products is completed. Therefore, the fruit and vegetable distribution optimization method based on the on-line scheduling system can save the calculation resources required by agricultural product distribution optimization, and solve the problems that excessive agricultural products are stored at a distribution destination and the accumulation and decay of the agricultural products are accelerated.
Example 2:
fig. 2 is a schematic structural diagram of an electronic device for implementing a fruit and vegetable distribution optimization method based on an on-line dispatching system according to an embodiment of the present invention.
The electronic device 1 may comprise a processor 10, a memory 11, a bus 12 and a communication interface 13, and may further comprise a computer program stored in the memory 11 and executable on the processor 10, such as a fruit and vegetable distribution optimization program under an on-line scheduling system.
The memory 11 includes at least one type of readable storage medium, including flash memory, a mobile hard disk, a multimedia card, a card memory (e.g., SD or DX memory, etc.), a magnetic memory, a magnetic disk, an optical disk, etc. The memory 11 may in some embodiments be an internal storage unit of the electronic device 1, such as a removable hard disk of the electronic device 1. The memory 11 may in other embodiments also be an external storage device of the electronic device 1, such as a plug-in mobile hard disk, a smart memory card (SmartMediaCard, SMC), a secure digital (SecureDigital, SD) card, a flash card (FlashCard) or the like, provided on the electronic device 1. Further, the memory 11 may also include both an internal storage unit and an external storage device of the electronic device 1. The memory 11 may be used not only for storing application software installed in the electronic device 1 and various data, such as codes based on fruit and vegetable distribution optimization programs under an on-line dispatching system, but also for temporarily storing data that has been output or is to be output.
The processor 10 may be comprised of integrated circuits in some embodiments, for example, a single packaged integrated circuit, or may be comprised of multiple integrated circuits packaged with the same or different functions, including one or more central processing units (CentralProcessingunit, CPU), microprocessors, digital processing chips, graphics processors, a combination of various control chips, and the like. The processor 10 is a control unit (control unit) of the electronic device, connects the respective components of the entire electronic device using various interfaces and lines, executes or executes programs or modules stored in the memory 11 (for example, fruit and vegetable distribution optimization programs under an on-line scheduling system, etc.), and invokes data stored in the memory 11 to perform various functions of the electronic device 1 and process data.
The bus may be an Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, or the like. The bus may be classified as an address bus, a data bus, a control bus, etc. The bus is arranged to enable a connection communication between the memory 11 and at least one processor 10 etc.
Fig. 2 shows only an electronic device with components, it being understood by a person skilled in the art that the structure shown in fig. 2 does not constitute a limitation of the electronic device 1, and may comprise fewer or more components than shown, or may combine certain components, or may be arranged in different components.
For example, although not shown, the electronic device 1 may further include a power source (such as a battery) for supplying power to each component, and preferably, the power source may be logically connected to the at least one processor 10 through a power management device, so that functions of charge management, discharge management, power consumption management, and the like are implemented through the power management device. The power supply may also include one or more of any of a direct current or alternating current power supply, recharging device, power failure detection circuit, power converter or inverter, power status indicator, etc. The electronic device 1 may further include various sensors, bluetooth modules, wi-Fi modules, etc., which will not be described herein.
Further, the electronic device 1 may also comprise a network interface, optionally the network interface may comprise a wired interface and/or a wireless interface (e.g. WI-FI interface, bluetooth interface, etc.), typically used for establishing a communication connection between the electronic device 1 and other electronic devices.
The electronic device 1 may optionally further comprise a user interface, which may be a Display, an input unit, such as a Keyboard (Keyboard), or a standard wired interface, a wireless interface. Alternatively, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (organic light-emitting diode) touch, or the like. The display may also be referred to as a display screen or display unit, as appropriate, for displaying information processed in the electronic device 1 and for displaying a visual user interface.
It should be understood that the embodiments described are for illustrative purposes only and are not limited to this configuration in the scope of the patent application.
The fruit and vegetable distribution optimization program stored in the memory 11 of the electronic device 1 and based on the on-line dispatching system is a combination of a plurality of instructions, and when running in the processor 10, the method can be implemented:
receiving a fruit and vegetable distribution optimizing instruction, determining fruits and vegetables to be distributed according to the fruit and vegetable distribution optimizing instruction, and storing refrigeration points of the fruits and vegetables to be distributed to obtain a first refrigeration point;
when fruits and vegetables to be distributed are transferred from a planting point to a first refrigerating point, an on-line dispatching system is utilized to receive picking data of the fruits and vegetables to be distributed, wherein the picking data comprise picking temperature of the fruits and vegetables to be distributed, picked from the planting point, and first transfer time of the fruits and vegetables to be distributed, transferred from the planting point to the first refrigerating point;
Determining an initial quantitative value of the quality of the fruits and vegetables to be distributed according to the first transfer time and the picking temperature;
analyzing a fruit and vegetable distribution optimizing instruction to obtain distribution destination points, and determining a plurality of distribution paths between the first refrigeration points and the distribution destination points, wherein the distribution paths consist of the first refrigeration points, the second refrigeration points, the ith refrigeration point of …, the mth refrigeration point and the distribution destination points, the distribution starting point of each distribution path is the first refrigeration point, the distribution end point is the distribution destination point, i is more than or equal to 1, and m is the total number of the refrigeration points included in the distribution paths;
obtaining distribution data of each distribution path, wherein the distribution data is obtained according to a first refrigeration point, a second refrigeration point, a … ith refrigeration point, an mth refrigeration point and a distribution destination point, and a distribution path selection function is constructed according to the distribution data and a quality initial quantization value;
solving each distribution path selection function to obtain a corresponding quality attenuation quantized value, selecting a minimum quantized value from all quality attenuation quantized values larger than zero, and determining a distribution path corresponding to the minimum quantized value as an optimal distribution path;
determining a client of a delivery destination point to obtain a delivery point client, connecting the delivery point client by using an online dispatching system, and obtaining the current storage quantity of the delivery destination point by using the delivery point client after the online dispatching system is successfully connected with the delivery point client, wherein the current storage quantity is determined by fruits and vegetables stored in the delivery destination point;
Obtaining the maximum storage amount of a delivery destination point and the fruit and vegetable amount of fruits and vegetables to be delivered to obtain the fruit and vegetable delivery amount, when the fruits and vegetables to be delivered start to be delivered based on the optimal delivery path, based on the maximum storage amount and the current storage amount, performing dynamic delivery on stored fruits and vegetables until the addition value of the current storage amount and the fruit and vegetable delivery amount is smaller than the maximum storage amount, completing dynamic delivery and obtaining an idle position point for storing the fruits and vegetables to be delivered;
and sending the idle position points to an online dispatching system, and notifying a transport system for transporting fruits and vegetables to be distributed by using the online dispatching system, so that the distribution optimization of agricultural products is completed.
Specifically, the specific implementation method of the above instruction by the processor 10 may refer to descriptions of related steps in the corresponding embodiments of fig. 1 to 2, which are not repeated herein.
Further, the modules/units integrated in the electronic device 1 may be stored in a computer readable storage medium if implemented in the form of software functional units and sold or used as separate products. The computer readable storage medium may be volatile or nonvolatile. For example, the computer readable medium may include: any entity or device capable of carrying the computer program code, a recording medium, a U disk, a removable hard disk, a magnetic disk, an optical disk, a computer memory, a Read-only memory (ROM).
The present invention also provides a computer readable storage medium storing a computer program which, when executed by a processor of an electronic device, can implement:
receiving a fruit and vegetable distribution optimizing instruction, determining fruits and vegetables to be distributed according to the fruit and vegetable distribution optimizing instruction, and storing refrigeration points of the fruits and vegetables to be distributed to obtain a first refrigeration point;
when fruits and vegetables to be distributed are transferred from a planting point to a first refrigerating point, an on-line dispatching system is utilized to receive picking data of the fruits and vegetables to be distributed, wherein the picking data comprise picking temperature of the fruits and vegetables to be distributed, picked from the planting point, and first transfer time of the fruits and vegetables to be distributed, transferred from the planting point to the first refrigerating point;
determining an initial quantitative value of the quality of the fruits and vegetables to be distributed according to the first transfer time and the picking temperature;
analyzing a fruit and vegetable distribution optimizing instruction to obtain distribution destination points, and determining a plurality of distribution paths between the first refrigeration points and the distribution destination points, wherein the distribution paths consist of the first refrigeration points, the second refrigeration points, the ith refrigeration point of …, the mth refrigeration point and the distribution destination points, the distribution starting point of each distribution path is the first refrigeration point, the distribution end point is the distribution destination point, i is more than or equal to 1, and m is the total number of the refrigeration points included in the distribution paths;
Obtaining distribution data of each distribution path, wherein the distribution data is obtained according to a first refrigeration point, a second refrigeration point, a … ith refrigeration point, an mth refrigeration point and a distribution destination point, and a distribution path selection function is constructed according to the distribution data and a quality initial quantization value;
solving each distribution path selection function to obtain a corresponding quality attenuation quantized value, selecting a minimum quantized value from all quality attenuation quantized values larger than zero, and determining a distribution path corresponding to the minimum quantized value as an optimal distribution path;
determining a client of a delivery destination point to obtain a delivery point client, connecting the delivery point client by using an online dispatching system, and obtaining the current storage quantity of the delivery destination point by using the delivery point client after the online dispatching system is successfully connected with the delivery point client, wherein the current storage quantity is determined by fruits and vegetables stored in the delivery destination point;
obtaining the maximum storage amount of a delivery destination point and the fruit and vegetable amount of fruits and vegetables to be delivered to obtain the fruit and vegetable delivery amount, when the fruits and vegetables to be delivered start to be delivered based on the optimal delivery path, based on the maximum storage amount and the current storage amount, performing dynamic delivery on stored fruits and vegetables until the addition value of the current storage amount and the fruit and vegetable delivery amount is smaller than the maximum storage amount, completing dynamic delivery and obtaining an idle position point for storing the fruits and vegetables to be delivered;
And sending the idle position points to an online dispatching system, and notifying a transport system for transporting fruits and vegetables to be distributed by using the online dispatching system, so that the distribution optimization of agricultural products is completed.
The modules described as separate components may or may not be physically separate, and components shown as modules may or may not be physical units, may be located in one place, or may be distributed over multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional module in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units can be realized in a form of hardware or a form of hardware and a form of software functional modules.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential characteristics thereof.
Finally, it should be noted that the above-mentioned embodiments are merely for illustrating the technical solution of the present invention and not for limiting the same, and although the present invention has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications and equivalents may be made to the technical solution of the present invention without departing from the spirit and scope of the technical solution of the present invention.

Claims (10)

1. The fruit and vegetable distribution optimization method based on the on-line scheduling system is characterized by comprising the following steps of:
receiving a fruit and vegetable distribution optimizing instruction, determining fruits and vegetables to be distributed according to the fruit and vegetable distribution optimizing instruction, and storing refrigeration points of the fruits and vegetables to be distributed to obtain a first refrigeration point;
when fruits and vegetables to be distributed are transferred from a planting point to a first refrigerating point, an on-line dispatching system is utilized to receive picking data of the fruits and vegetables to be distributed, wherein the picking data comprise picking temperature of the fruits and vegetables to be distributed, picked from the planting point, and first transfer time of the fruits and vegetables to be distributed, transferred from the planting point to the first refrigerating point;
determining an initial quantitative value of the quality of the fruits and vegetables to be distributed according to the first transfer time and the picking temperature;
analyzing a fruit and vegetable distribution optimizing instruction to obtain distribution destination points, and determining a plurality of distribution paths between the first refrigeration points and the distribution destination points, wherein the distribution paths consist of the first refrigeration points, the second refrigeration points, the ith refrigeration point of …, the mth refrigeration point and the distribution destination points, the distribution starting point of each distribution path is the first refrigeration point, the distribution end point is the distribution destination point, i is more than or equal to 1, and m is the total number of the refrigeration points included in the distribution paths;
Obtaining distribution data of each distribution path, wherein the distribution data is obtained according to a first refrigeration point, a second refrigeration point, a … ith refrigeration point, an mth refrigeration point and a distribution destination point, and a distribution path selection function is constructed according to the distribution data and a quality initial quantization value;
solving each distribution path selection function to obtain a corresponding quality attenuation quantized value, selecting a minimum quantized value from all quality attenuation quantized values larger than zero, and determining a distribution path corresponding to the minimum quantized value as an optimal distribution path;
determining a client of a delivery destination point to obtain a delivery point client, connecting the delivery point client by using an online dispatching system, and obtaining the current storage quantity of the delivery destination point by using the delivery point client after the online dispatching system is successfully connected with the delivery point client, wherein the current storage quantity is determined by fruits and vegetables stored in the delivery destination point;
obtaining the maximum storage amount of a delivery destination point and the fruit and vegetable amount of fruits and vegetables to be delivered to obtain the fruit and vegetable delivery amount, when the fruits and vegetables to be delivered start to be delivered based on the optimal delivery path, based on the maximum storage amount and the current storage amount, performing dynamic delivery on stored fruits and vegetables until the addition value of the current storage amount and the fruit and vegetable delivery amount is smaller than the maximum storage amount, completing dynamic delivery and obtaining an idle position point for storing the fruits and vegetables to be delivered;
And sending the idle position points to an online dispatching system, and notifying a transport system for transporting fruits and vegetables to be distributed by using the online dispatching system, so that the distribution optimization of agricultural products is completed.
2. The optimization method for fruit and vegetable distribution based on an on-line dispatching system according to claim 1, wherein the determining the initial quantitative value of the quality of the fruit and vegetable to be distributed according to the first transfer time and the picking temperature comprises:
mapping and normalizing the first transfer time and the picking temperature to obtain normalized first transfer time and picking temperature;
calculating to obtain an initial quantitative value of the quality of the fruits and vegetables to be distributed according to the following formula:
wherein ,q0 An initial quantized value representing the quality of the fruit and vegetable to be dispensed,representing quality standard quantized values of fruits and vegetables to be dispensed, alpha represents weight factors of a calculation formula of quality initial quantized values, T 0 Representing the normalized picking temperature, t 0 Indicating the normalized first transfer time.
3. The method for optimizing fruit and vegetable distribution based on an on-line dispatching system according to claim 2, wherein the step of obtaining the distribution data of each distribution path comprises the steps of:
sequentially acquiring historical delivery time from a first refrigeration point to a second refrigeration point, …, an i-1 refrigeration point to an i refrigeration point, …, an m refrigeration point and a delivery destination point from a historical database in an online dispatching system;
Calculating average delivery time from the first refrigeration point to the second refrigeration point, …, from the i-1 refrigeration point to the i refrigeration point, …, from the m refrigeration point and the delivery destination according to the historical delivery time, and obtaining first delivery time, …, i delivery time, … and m delivery time;
determining the time when the fruits and vegetables to be dispensed leave the first refrigeration point to obtain the dispensing start time, and respectively predicting the dispensing time periods from the first refrigeration point to the second refrigeration point, …, from the i-1 refrigeration point to the i refrigeration point, …, from the m refrigeration point and from the dispensing destination point based on the dispensing start time and the total length of the dispensing path to obtain a first time period, …, an i time period, … and an m time period;
starting a weather temperature system bound with the online dispatching system, and respectively predicting average temperatures of a first time period, …, an i-th time period, … and an m-th time period by using the weather temperature system to obtain a first average temperature, …, an i-th average temperature, … and an m-th average temperature;
and summarizing the first delivery time, …, the ith delivery time, … and the mth delivery time, and the first average temperature, …, the ith average temperature, … and the mth average temperature to obtain delivery data of each delivery path.
4. The optimization method for fruit and vegetable distribution based on an on-line dispatching system as set forth in claim 3, wherein the constructing a distribution path selection function according to the distribution data and the quality initial quantization value comprises:
mapping and normalizing the distribution data to obtain normalized distribution data;
and constructing the following distribution path selection function by using the normalized distribution data and the quality initial quantized value:
wherein ,f(ti ,T i ) Represent the delivery path selection function, q m Representing the quantized value of the mass attenuation obtained by calculating the distribution path selection function, t i Representing the delivery time from the ith refrigeration point to the (i+1) th refrigeration point after normalization, namely the ith delivery time after normalization, T i Represents the average temperature from the ith refrigeration point to the (i+1) th refrigeration point after normalization, namely the ith average temperature after normalization, beta i At t i Fluctuation factor of G i Is T i And beta i And G i The values of (2) are all greater than zero and less than or equal to 1, and beta i And G i The generation rule of (2) accords with a normal function.
5. The method for optimizing fruit and vegetable distribution based on an on-line scheduling system according to claim 4, wherein the step of dynamically delivering the stored fruits and vegetables to the warehouse further comprises:
Judging the addition value of the fruit and vegetable distribution amount and the current storage amount, and the size relation of the addition value and the maximum storage amount;
if the sum of the fruit and vegetable delivery amount and the current storage amount is smaller than or equal to the maximum storage amount, the stored fruit and vegetable does not need to be dynamically delivered out of the warehouse, and a delivery destination point is obtained and used for storing idle position points of the fruit and vegetable to be delivered;
when the idle position points are successfully obtained, directly distributing fruits and vegetables to be distributed to the idle position points;
and if the sum of the fruit and vegetable delivery quantity and the current storage quantity is larger than the maximum storage quantity, when the fruit and vegetable to be delivered starts to be delivered based on the optimal delivery path, the stored fruit and vegetable is dynamically delivered.
6. The optimization method for fruit and vegetable delivery based on an on-line dispatching system according to claim 5, wherein when the fruit and vegetable to be delivered starts to be delivered based on the optimal delivery path, the method for dynamically delivering the stored fruit and vegetable to be delivered from the warehouse based on the maximum storage amount and the current storage amount comprises:
when the fruits and vegetables to be distributed start to be distributed based on the optimal distribution path, acquiring the distribution starting time;
when the delivery starting time is successfully obtained, determining a delivery position point of the stored fruits and vegetables, and calculating to obtain the damage rate of the fruits and vegetables for conveying the stored fruits and vegetables to the delivery position point;
Presetting a delivery starting time and a delivery speed for starting to execute delivery of stored fruits and vegetables, and constructing a dynamic delivery optimization model of the delivery starting time and the delivery speed based on the fruit and vegetable damage rate;
constructing a dynamic ex-warehouse constraint function of a dynamic ex-warehouse optimization model based on the maximum storage amount and the current storage amount;
on the premise of a dynamic ex-warehouse constraint function, solving a dynamic ex-warehouse optimization model to obtain an optimal value of ex-warehouse starting time and an optimal value of ex-warehouse speed;
and after the time reaches the optimal value of the delivery start time, performing dynamic delivery of the stored fruits and vegetables on the basis of the optimal value of the delivery speed.
7. The method for optimizing fruit and vegetable distribution based on an on-line dispatching system according to claim 6, wherein the constructing a dynamic delivery optimization model of delivery start time and delivery speed based on fruit and vegetable damage rate comprises:
calculating the time when the fruits and vegetables to be delivered reach the delivery destination point, and obtaining the delivery destination time;
based on the ex-warehouse end time and the ex-warehouse start time, a dynamic ex-warehouse optimization model is constructed, wherein the dynamic ex-warehouse optimization model is as follows:
μ∝v(t)
wherein ,indicating the start time of delivery of the stored fruits and vegetables at the delivery destination point >Indicating the delivery end time of the fruit and vegetable to be delivered to the delivery destination point,/day>The method comprises the steps of representing a quality loss quantized value of stored fruits and vegetables reaching a delivery position point from a delivery destination point, wherein gamma represents a fruit and vegetable damage rate of the stored fruits and vegetables, W (t) represents delivery quantity of the stored fruits and vegetables delivered from the delivery destination point at a time t, v (t) represents delivery speed of the stored fruits and vegetables delivered from the delivery destination point at the time t, oc represents positive correlation, mu is a weight factor of the fruit and vegetable damage rate, mu is greater than or equal to 1, and is in positive correlation with v (t), and mu is greater when v (t) is greater.
8. The fruit and vegetable distribution optimization method based on an on-line scheduling system according to claim 7, wherein the dynamic ex-warehouse constraint function is composed of a first ex-warehouse constraint function, a second ex-warehouse constraint function and a third ex-warehouse constraint function, wherein the first ex-warehouse constraint function is:
s.t.W c +W m ≥W k
wherein ,Wc Representing the current storage quantity, W m Representing the fruit and vegetable distribution amount, W k Indicating the maximum storage amount of the delivery destination point.
9. The fruit and vegetable distribution optimization method based on an on-line scheduling system according to claim 8, wherein the construction of the second ex-warehouse constraint function comprises:
Calculating the distance between the delivery destination point and the delivery position point to obtain delivery length;
calculating the time to the warehouse end point of the stored fruits and vegetables reaching the warehouse-out position point based on the warehouse-out length and the warehouse-out speed, wherein the calculation method of the time to the warehouse end point is as follows:
wherein ,indicating the time to the end of the warehouse of the stored fruit and vegetable to the point of the delivery site, < >>Indicating the start time of delivery of the stored fruits and vegetables at the delivery destination point>Represents the average speed of delivery calculated from v (t), l c Representing a library length;
constructing a second ex-warehouse constraint function according to the time to the warehouse end point and the time to the ex-warehouse end point, wherein the second ex-warehouse constraint function is as follows:
wherein ,the delivery start time at which the delivery of the fruit and vegetable to be delivered is started is indicated.
10. The fruit and vegetable distribution optimization method based on an on-line scheduling system according to claim 9, wherein the third ex-warehouse constraint function is:
s.t.W c ≤W a ,W m ≤W a +W k -W c
wherein ,Wa Is shown inTo->And (3) total delivery of the stored fruits and vegetables from the delivery destination point to the delivery position point in the time period.
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