CN112907193A - Intelligent logistics transportation management system based on big data and Internet of things - Google Patents
Intelligent logistics transportation management system based on big data and Internet of things Download PDFInfo
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Abstract
The invention relates to an intelligent logistics transportation management system based on big data and Internet of things, which comprises: the system comprises a logistics transportation server, logistics transportation terminals and a database, wherein the logistics transportation server is in communication connection with the database and each logistics transportation terminal respectively. The logistics transportation server comprises: the system comprises a transportation networking unit, an initialization unit, a transportation path unit and a path optimization unit, wherein communication connection is arranged among the units. And establishing a space-time logistics transportation network, and acquiring a logistics transportation path of each logistics transportation vehicle according to the transportation time attribute value and the transportation position attribute value to obtain a logistics transportation path sequence of each logistics transportation vehicle. And acquiring the path goodness of each logistics transportation path according to the first transportation coefficient, the second transportation coefficient, the third transportation coefficient, the cargo transportation time, the cargo waiting transportation time and the cargo transportation waiting time, and then taking the logistics transportation path with the maximum path goodness in the logistics transportation path sequence as the optimal logistics transportation path.
Description
Technical Field
The invention relates to the field of big data and logistics management, in particular to an intelligent logistics transportation management system based on big data and the Internet of things.
Background
Under the control of the information system, the intelligent logistics system operates each link of the logistics system to realize comprehensive perception of the system, so that various problems can be timely handled and timely and necessary self-adjustment can be carried out. The logistics is automated, innovative and accurate by utilizing the cross fusion of the information technology and the logistics technology. The modern comprehensive logistics system comprises comprehensive analysis, timely processing and self-adjusting functions, and achieves logistics regulation intelligence, discovery intelligence, innovation intelligence and system intelligence.
With the popularization of the RFID technology and the sensor network of the Internet of things, the interconnection and intercommunication of objects and objects lay a foundation for the intelligent integration of a logistics system, a production system, a purchasing system and a selling system of an enterprise.
The development and the transformation of the logistics industry are promoted by the high-speed development of the e-commerce industry, however, the complexity of the logistics scene increases the difficulty of the logistics transportation, so that the multi-objective logistics transportation scene needs to be upgraded, and the efficiency of the logistics transportation needs to be optimized and improved.
Disclosure of Invention
In view of the above, the invention provides an intelligent logistics transportation management system based on big data and internet of things, which comprises a logistics transportation server, logistics transportation terminals and a database, wherein the logistics transportation server is in communication connection with the database and each logistics transportation terminal respectively. The logistics transportation server comprises: the system comprises a transportation networking unit, an initialization unit, a transportation path unit and a path optimization unit, wherein communication connection is formed among the units;
the transportation networking unit acquires all stations of the whole logistics transportation and connects all the stations by line segments to establish a space-time logistics transportation network;
the method comprises the steps that an initialization unit obtains preset iteration times, a logistics updating period, a logistics transportation period, a first transportation coefficient, a second transportation coefficient and a third transportation coefficient, and discretization processing is carried out on the logistics transportation period according to the logistics updating period to obtain a logistics transportation time sequence;
the method comprises the following steps that a transportation path unit randomly places a first preset number of logistics transport vehicles on a second preset number of cargo storage sites in a space-time logistics transportation network, initializes a transportation time attribute value and a transportation position attribute value of each logistics transport vehicle, and sets the number of times of completing iteration to be zero;
the path optimization unit acquires the logistics transportation path of each logistics transportation vehicle in the iteration process according to the transportation time attribute value and the transportation position attribute value of each logistics transportation vehicle; judging whether each logistics transport vehicle reaches the logistics transport homing site or not according to the transport position attribute value of each logistics transport vehicle, and outputting the logistics transport path of each logistics transport vehicle in the iteration process when all the logistics transport vehicles reach the logistics transport homing site;
the path optimization unit acquires the path goodness of the logistics transportation path of each logistics transportation vehicle according to the first transportation coefficient, the second transportation coefficient, the third transportation coefficient, the cargo transportation time, the cargo transportation waiting time and the cargo transportation waiting time; adding one to the number of iterations completed, and comparing the number of iterations completed with a preset number of iterations; stopping iteration when the iteration times are larger than or equal to the preset iteration times, and outputting a group of logistics transportation path sequences for each logistics transportation vehicle;
the path optimization unit acquires the path goodness of each logistics transportation path in the logistics transportation path sequence, takes the logistics transportation path with the maximum path goodness in the logistics transportation path sequence as the optimal logistics transportation path of each logistics transportation vehicle, and sends the optimal logistics transportation path to the corresponding logistics transportation terminal.
In a further embodiment, the obtaining, by the path optimization unit, the logistics transportation path of the logistics transportation vehicle according to the transportation time attribute value and the transportation position attribute value of the logistics transportation vehicle includes:
the path optimization unit initializes the transport time attribute value of each logistics transport vehicle to zero, and obtains the transport position attribute value of the logistics transport vehicle when the transport time attribute value of the logistics transport vehicle is zero; initializing a logistics transportation space-time network according to the transportation position attribute value of the logistics transportation vehicle when the transportation time attribute value of the logistics transportation vehicle is zero so as to obtain a starting point of each logistics transportation vehicle in the space-time logistics transportation network; at the starting point of the logistics transport vehicle, the transport time attribute value of the logistics transport vehicle is zero, and the transport position attribute value is zero;
the path optimization unit generates a transportation schedule for each logistics transport vehicle, and each logistics transport vehicle corresponds to one transportation schedule; the transportation scheduling table stores goods warehousing sites passed by the logistics transport vehicle;
when the logistics transport vehicle reaches one goods storage site, the path optimization unit acquires the residual cargo capacity of the logistics transport vehicle, and when the residual cargo capacity is larger than zero, the transfer probability of the logistics transport vehicle from the current goods storage site to each other goods storage site is obtained according to the logistics transport departure site and the logistics transport arrival site of each goods in the logistics transport vehicle;
the path optimization unit selects the goods warehousing station with the maximum transfer probability as the next arriving goods warehousing station of the logistics transport vehicle, adds the goods warehousing station where the current logistics transport vehicle is located into the transportation scheduling table, and updates the residual cargo capacity of the logistics transport vehicle; the transfer probability of the goods warehousing station in the transportation scheduling table is zero;
the path optimization unit acquires a transportation time attribute value and a transportation position attribute value of the logistics transport vehicle, compares the transportation position attribute value with a position value of the logistics transport homing site, and compares the transportation time attribute value with the length of the logistics transportation time sequence when the transportation position attribute value is not equal to the position value of the logistics transport homing site;
and when the transportation time attribute value is greater than or equal to the length of the logistics transportation time sequence, the path optimization unit moves the logistics transportation vehicle to the logistics transportation homing station, updates the transportation position attribute value of the logistics transportation vehicle to the position value of the logistics transportation homing station, and obtains the logistics transportation path of each logistics transportation vehicle according to the transportation scheduling table of each logistics transportation vehicle.
In a further embodiment, the obtaining of the logistics transportation time sequence by discretizing the logistics transportation period according to the logistics update period by the initializing unit includes:
T＝[T1,T2,T3…Tn]
△T＝Ti+1-Ti
t is logistics transportation time sequence, delta T is logistics updating period, TiFor the ith logistics transportation time point, Ti+1Is the (i + 1) th logistics transportation time point, and i is the index of the logistics transportation time point.
In a further embodiment, the goods warehousing site is a site for warehousing goods. The logistics transportation departure site is a delivery starting point of goods during logistics transportation. And when the logistics transportation arrival station is used for logistics transportation, the delivery end point of the goods is obtained. The logistics transportation homing site is a reporting site when the logistics transportation vehicle completes one transportation.
In a further embodiment, the logistics transportation terminal is a device with a communication function and a data transmission function, which is used by a driver of a logistics transportation vehicle, and comprises: smart phones, tablet computers, and smart watches. The logistics transportation period is the daily transportation time of each logistics transportation vehicle, and the logistics updating period is the time interval for discretizing the logistics transportation period. The transportation schedule of the logistics transportation vehicle is used for representing the logistics transportation track of the logistics transportation vehicle. The logistics transportation path sequence comprises logistics transportation paths output by the same logistics transportation vehicle in each iteration process.
In a further embodiment, the logistics transportation time sequence comprises a plurality of logistics transportation time points arranged according to a time sequence, and each logistics transportation time point corresponds to a time. The freight transportation time is the total time for each logistics transport vehicle to transport the freight. The waiting transportation time of the goods is the waiting time of the goods before transportation. The cargo transportation waiting time is the waiting time of the cargos after transportation.
In a further embodiment, all the goods warehousing sites in the transportation schedule are used as the transportation prohibition sites, and the transportation prohibition sites are the goods warehousing sites which are already passed through and are not passed through any more. The first transportation coefficient is the weighted value of the transportation time of the goods, and the second transportation coefficient is the weighted value of the waiting transportation time of the goods; the third transportation coefficient is a weighted value of the cargo transportation waiting time.
In a further embodiment, the obtaining, by the path optimization unit, the transition probability of the logistics transportation vehicle from the current cargo warehousing site to each of the other cargo warehousing sites according to the logistics transportation departure site and the logistics transportation arrival site of each of the cargos in the logistics transportation vehicle includes:
the path optimization unit acquires a logistics transportation departure site and a logistics transportation arrival site of each cargo in the logistics transport vehicle, and acquires a cargo storage site passing through a space between the logistics transportation departure site and the logistics transportation arrival site of each cargo to obtain a site passing table of each cargo in the logistics transport vehicle;
the route optimization unit counts the occurrence frequency of each goods warehousing site according to the site route tables of all goods, and obtains the transfer coefficient from the current goods warehousing site to each other goods warehousing site according to the occurrence frequency of each goods warehousing site;
and the path optimization unit calculates the transfer probability from the current goods warehousing site to each other goods warehousing site according to the transfer coefficient from the current goods warehousing site to each other goods warehousing site.
In a further embodiment, the transition probability is calculated as
Wherein, PtTransition probability, R, for the t-th cargo storage sitetFor the transfer coefficient of the t-th cargo storage site, RkAnd (4) the transfer coefficient of the kth goods warehousing site, wherein k is the index of the goods warehousing site, and m is the number of the goods warehousing sites.
The invention establishes the space-time logistics transportation network by connecting the stations, selects a logistics transportation path with the maximum path goodness for each logistics transportation vehicle as the optimal logistics transportation path according to the space-time logistics transportation network, and transports goods by the logistics transportation vehicles according to the optimal logistics transportation path, thereby being capable of adapting to the arrangement of intelligent multi-target logistics scheduling.
Drawings
Fig. 1 is a block diagram illustrating an intelligent logistics transportation management system based on big data and internet of things according to an exemplary embodiment.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments herein without making any creative effort, shall fall within the scope of protection.
Referring to fig. 1, in one embodiment, an intelligent logistics transportation management system based on big data and internet of things includes a logistics transportation server, a logistics transportation terminal and a database. The logistics transportation server has communication connection with database and each logistics transportation terminal respectively, and the logistics transportation server includes: the system comprises a transportation networking unit, an initialization unit, a transportation path unit and a path optimization unit, wherein communication connection is formed among the units;
the transportation networking unit acquires all stations of the whole logistics transportation and connects all the stations by line segments to establish a space-time logistics transportation network;
the method comprises the steps that an initialization unit obtains preset iteration times, a logistics updating period, a logistics transportation period, a first transportation coefficient, a second transportation coefficient and a third transportation coefficient, and discretization processing is carried out on the logistics transportation period according to the logistics updating period to obtain a logistics transportation time sequence;
the method comprises the following steps that a transportation path unit randomly places a first preset number of logistics transport vehicles on a second preset number of cargo storage sites in a space-time logistics transportation network, initializes a transportation time attribute value and a transportation position attribute value of each logistics transport vehicle, and sets the number of times of completing iteration to be zero;
the path optimization unit acquires the logistics transportation path of each logistics transportation vehicle in the iteration process according to the transportation time attribute value and the transportation position attribute value of each logistics transportation vehicle; judging whether each logistics transport vehicle reaches the logistics transport homing site or not according to the transport position attribute value of each logistics transport vehicle, and outputting the logistics transport path of each logistics transport vehicle in the iteration process when all the logistics transport vehicles reach the logistics transport homing site;
the path optimization unit acquires the path goodness of the logistics transportation path of each logistics transportation vehicle according to the first transportation coefficient, the second transportation coefficient, the third transportation coefficient, the cargo transportation time, the cargo transportation waiting time and the cargo transportation waiting time; adding one to the number of iterations completed, and comparing the number of iterations completed with a preset number of iterations; stopping iteration when the iteration times are larger than or equal to the preset iteration times, and outputting a group of logistics transportation path sequences for each logistics transportation vehicle;
the path optimization unit acquires the path goodness of each logistics transportation path in the logistics transportation path sequence, takes the logistics transportation path with the maximum path goodness in the logistics transportation path sequence as the optimal logistics transportation path of each logistics transportation vehicle, and sends the optimal logistics transportation path to the corresponding logistics transportation terminal.
The working principle of the present invention is explained below. In one embodiment, the logistics transportation optimization method executed by the intelligent logistics transportation management system comprises the following steps:
and S1, the transportation networking unit acquires all stations of the whole logistics transportation and connects all the stations by line segments to establish a space-time logistics transportation network.
In one embodiment, the sites include a cargo warehousing site, a logistics transportation departure site, a logistics transportation arrival site and a logistics transportation return site, and a connecting line between the sites in the logistics transportation network is a transportation path between the sites, wherein one site can be one or more of the cargo warehousing site, the logistics transportation departure site and the logistics transportation arrival site at the same time.
In one embodiment, the goods warehousing site is a site for warehousing goods. The logistics transportation departure site is a delivery starting point of goods when logistics transportation is carried out. And when the logistics transportation arriving station is logistics transportation, the delivery end point of the goods is reached. The logistics transportation homing site is a reporting site when the logistics transportation vehicle completes one transportation.
S2, the initialization unit obtains the preset iteration number, the logistics updating period, the logistics transportation period, the first transportation coefficient, the second transportation coefficient and the third transportation coefficient, and discretizes the logistics transportation period according to the logistics updating period to obtain the logistics transportation time sequence.
In one embodiment, the logistics transportation period is the daily transportation time of each logistics transportation vehicle, and the logistics updating period is a time interval for discretizing the logistics transportation period. The preset iteration times are preset times needing iteration.
The initialization unit discretizes the logistics transportation period according to the logistics updating period to obtain a logistics transportation time sequence, and the method comprises the following steps:
T＝[T1,T2,T3…Tn]
△T＝Ti+1-Ti
t is logistics transportation time sequence, delta T is logistics updating period, TiFor the ith logistics transportation time point, Ti+1Is the (i + 1) th logistics transportation time point, and i is the index of the logistics transportation time point.
The freight transportation time is the total time for each logistics transport vehicle to transport the freight. The cargo waiting transport time is the waiting time of the cargo before transport. The cargo transportation waiting time is the waiting time of the cargo after transportation. The first transportation coefficient is the weighted value of the transportation time of the goods, and the second transportation coefficient is the weighted value of the waiting transportation time of the goods; the third transportation coefficient is a weighted value of the cargo transportation waiting time. The logistics transportation time sequence comprises a plurality of logistics transportation time points which are arranged according to the time sequence, and each logistics transportation time point corresponds to one moment.
S3, the transportation path unit randomly places the first preset number of logistics transportation vehicles on the second preset number of cargo storage sites in the space-time logistics transportation network, initializes the transportation time attribute value and the transportation position attribute value of each logistics transportation vehicle, and sets the number of iterations to zero.
In one embodiment, the number of iterations completed is the number of iterations that have been performed. The first preset quantity is the quantity of the logistics transport vehicles, and the second preset quantity is the quantity of the goods warehousing stations. And the transportation time attribute value of the logistics transport vehicle is the current logistics transportation time point of the logistics transport vehicle. And the transportation position attribute value of the logistics transport vehicle is the current time point of the logistics transport vehicle.
S4, the path optimization unit obtains the logistics transportation path of each logistics transportation vehicle in the iteration process according to the transportation time attribute value and the transportation position attribute value of each logistics transportation vehicle; and judging whether each logistics transport vehicle reaches the logistics transport homing site or not according to the transport position attribute value of each logistics transport vehicle, and outputting the logistics transport path of each logistics transport vehicle in the iteration process when all the logistics transport vehicles reach the logistics transport homing site.
S4.1, initializing the transportation time attribute value of each logistics transport vehicle to zero by a path optimization unit, and acquiring a transportation position attribute value of the logistics transport vehicle when the transportation time attribute value of the logistics transport vehicle is zero; initializing a logistics transportation space-time network according to the transportation position attribute value of the logistics transportation vehicle when the transportation time attribute value of the logistics transportation vehicle is zero so as to obtain a starting point of each logistics transportation vehicle in the space-time logistics transportation network; and at the starting point of the logistics transport vehicle, the transport time attribute value of the logistics transport vehicle is zero, and the transport position attribute value is zero.
And S4.2, generating a transportation schedule table for each logistics transport vehicle by the path optimization unit, wherein each logistics transport vehicle corresponds to one transportation schedule table.
The transportation scheduling table stores the passed goods warehousing sites of the logistics transport vehicle, all the goods warehousing sites in the transportation scheduling table are used as the transportation prohibition sites, the transportation prohibition sites are the passed goods warehousing sites which are not passed any more, and namely the transfer probability of the goods warehousing sites in the transportation scheduling table is zero.
S4.3, when the logistics transport vehicle reaches one goods storage site, the path optimization unit obtains the residual cargo capacity of the logistics transport vehicle, and when the residual cargo capacity is larger than zero, the transfer probability of the logistics transport vehicle from the current goods storage site to each other goods storage site is obtained according to the logistics transport departure site and the logistics transport arrival site of each goods in the logistics transport vehicle.
S4.4, the path optimization unit selects the goods storage site with the maximum transfer probability as a next arriving goods storage site of the logistics transport vehicle, adds the goods storage site of the current logistics transport vehicle into a transport scheduling table, and updates the residual cargo capacity of the logistics transport vehicle; the transition probability of the goods warehousing site in the transportation schedule is zero.
And S4.5, the path optimization unit acquires the transportation time attribute value and the transportation position attribute value of the logistics transport vehicle, compares the transportation position attribute value with the position value of the logistics transport homing site, and compares the transportation time attribute value with the length of the logistics transport time sequence when the transportation position attribute value is not equal to the position value of the logistics transport homing site.
S4.6, when the transportation time attribute value is larger than or equal to the length of the logistics transportation time sequence, the path optimization unit moves the logistics transportation vehicle to the logistics transportation homing site, and updates the transportation position attribute value of the logistics transportation vehicle to the position value of the logistics transportation homing site; and when the transport time attribute value is smaller than the length of the logistics transport time sequence, adding one to the transport time attribute value of the logistics transport vehicle.
And repeating the steps S4.3-S4.6 until all the logistics transport vehicles reach the logistics transport homing site, and obtaining the logistics transport path of each logistics transport vehicle according to the transport schedule of each logistics transport vehicle.
The transportation schedule of the logistics transportation vehicle is used for representing the logistics transportation path of the logistics transportation vehicle.
In one embodiment, the obtaining, by the path optimization unit, a transition probability of the logistics transportation vehicle from the current cargo warehousing site to each of the other cargo warehousing sites according to the logistics transportation departure site and the logistics transportation arrival site of each of the cargos in the logistics transportation vehicle includes:
the path optimization unit acquires a logistics transportation departure site and a logistics transportation arrival site of each cargo in the logistics transport vehicle, and acquires a cargo storage site passing through a space between the logistics transportation departure site and the logistics transportation arrival site of each cargo to obtain a site passing table of each cargo in the logistics transport vehicle;
the route optimization unit counts the occurrence frequency of each goods warehousing site according to the site route tables of all goods, and obtains the transfer coefficient from the current goods warehousing site to each other goods warehousing site according to the occurrence frequency of each goods warehousing site;
and the path optimization unit calculates the transfer probability from the current goods warehousing site to each other goods warehousing site according to the transfer coefficient from the current goods warehousing site to each other goods warehousing site.
In one embodiment, the transition probability is calculated as
Wherein, PtTransition probability, R, for the t-th cargo storage sitetFor the transfer coefficient of the t-th cargo storage site, RkAnd (4) the transfer coefficient of the kth goods warehousing site, wherein k is the index of the goods warehousing site, and m is the number of the goods warehousing sites.
S5, the path optimization unit obtains the path goodness of the logistics transportation path of each logistics transportation vehicle according to the first transportation coefficient, the second transportation coefficient, the third transportation coefficient, the cargo transportation time, the cargo waiting transportation time and the cargo transportation waiting time; adding one to the number of iterations completed, comparing the number of iterations completed with a preset number of iterations, and executing step S4 when the number of iterations completed is less than the preset number of iterations; and terminating the iteration when the iteration number is larger than or equal to the preset iteration number, and outputting a group of logistics transportation path sequences for each logistics transportation vehicle.
The logistics transportation path sequence comprises logistics transportation paths output by the same logistics transportation vehicle in each iteration process.
S6, the path optimization unit obtains the path goodness of each logistics transportation path in the logistics transportation path sequence, takes the logistics transportation path with the maximum path goodness in the logistics transportation path sequence as the optimal logistics transportation path of each logistics transportation vehicle, and sends the optimal logistics transportation path of each logistics transportation vehicle to the corresponding logistics transportation terminal.
The calculation formula of the path goodness is as follows:
u＝αt1+βt2+γt3
wherein u is the route goodness, α is the first transport coefficient, β is the second transport coefficient, γ is the third transport coefficient, t1For time of transport of goods, t2Waiting for the transport time for the goods, t3Waiting for the cargo transportation.
The logistics transportation terminal is the equipment that has communication function and data transmission function that the driver of logistics transport vehicle used, and it includes: smart phones, tablet computers, and smart watches.
According to the invention, the stations are connected to establish the space-time logistics transportation network, the logistics transportation path with the maximum path goodness is selected for each logistics transportation vehicle according to the space-time logistics transportation network to serve as the optimal logistics transportation path, and the logistics transportation vehicles transport goods according to the optimal logistics transportation path, so that the logistics transportation efficiency is greatly improved, the intelligent multi-target logistics scheduling arrangement is carried out, and the cost of a logistics company is saved.
In addition, functional units in the embodiments herein may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention essentially or partially contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product stored in a storage medium, which includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method described in the embodiments of the present invention, and the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (8)
1. The utility model provides an wisdom commodity circulation transportation management system based on big data and thing networking which characterized in that, it includes: the system comprises a logistics transportation server, logistics transportation terminals and a database, wherein the logistics transportation server is in communication connection with the database and each logistics transportation terminal respectively; the logistics transportation server comprises: the system comprises a transportation networking unit, an initialization unit, a transportation path unit and a path optimization unit, wherein communication connection is formed among the units;
the transportation networking unit acquires all stations of the whole logistics transportation and connects all the stations by line segments to establish a space-time logistics transportation network;
the method comprises the steps that an initialization unit obtains preset iteration times, a logistics updating period, a logistics transportation period, a first transportation coefficient, a second transportation coefficient and a third transportation coefficient, and discretization processing is carried out on the logistics transportation period according to the logistics updating period to obtain a logistics transportation time sequence;
the method comprises the following steps that a transportation path unit randomly places a first preset number of logistics transport vehicles on a second preset number of cargo storage sites in a space-time logistics transportation network, initializes a transportation time attribute value and a transportation position attribute value of each logistics transport vehicle, and sets the number of times of completing iteration to be zero;
the path optimization unit acquires the logistics transportation path of each logistics transportation vehicle in the iteration process according to the transportation time attribute value and the transportation position attribute value of each logistics transportation vehicle; judging whether each logistics transport vehicle reaches the logistics transport homing site or not according to the transport position attribute value of each logistics transport vehicle, and outputting the logistics transport path of each logistics transport vehicle in the iteration process when all the logistics transport vehicles reach the logistics transport homing site;
the path optimization unit acquires the path goodness of the logistics transportation path of each logistics transportation vehicle according to the first transportation coefficient, the second transportation coefficient, the third transportation coefficient, the cargo transportation time, the cargo transportation waiting time and the cargo transportation waiting time; adding one to the number of iterations completed, and comparing the number of iterations completed with a preset number of iterations; stopping iteration when the iteration times are larger than or equal to the preset iteration times, and outputting a group of logistics transportation path sequences for each logistics transportation vehicle;
the path optimization unit acquires the path goodness of each logistics transportation path in the logistics transportation path sequence, takes the logistics transportation path with the maximum path goodness in the logistics transportation path sequence as the optimal logistics transportation path of each logistics transportation vehicle, and sends the optimal logistics transportation path to the corresponding logistics transportation terminal.
2. The system of claim 1, wherein the logistics transportation terminal is a device having a communication function and a data transmission function used by a driver of the logistics transportation vehicle, and comprises: smart phones, tablet computers, and smart watches.
3. The system according to claim 1 or 2, wherein the logistics transportation period is a daily transportation time of each logistics transportation vehicle, and the logistics update period is a time interval for discretizing the logistics transportation period.
4. The system according to one of claims 1 to 3, wherein the path optimization unit obtaining the logistics transportation path of the logistics transportation vehicle according to the transportation time attribute value and the transportation position attribute value of the logistics transportation vehicle comprises:
the path optimization unit initializes the transport time attribute value of each logistics transport vehicle to zero, and obtains the transport position attribute value of the logistics transport vehicle when the transport time attribute value of the logistics transport vehicle is zero; initializing a logistics transportation space-time network according to the transportation position attribute value of the logistics transportation vehicle when the transportation time attribute value of the logistics transportation vehicle is zero so as to obtain a starting point of each logistics transportation vehicle in the space-time logistics transportation network;
the path optimization unit generates a transportation schedule for each logistics transport vehicle, and each logistics transport vehicle corresponds to one transportation schedule;
when the logistics transport vehicle reaches one goods storage site, the path optimization unit acquires the residual cargo capacity of the logistics transport vehicle, and when the residual cargo capacity is larger than zero, the transfer probability of the logistics transport vehicle from the current goods storage site to each other goods storage site is obtained according to the logistics transport departure site and the logistics transport arrival site of each goods in the logistics transport vehicle;
the path optimization unit selects the goods warehousing station with the maximum transfer probability as the next arriving goods warehousing station of the logistics transport vehicle, adds the goods warehousing station where the current logistics transport vehicle is located into the transportation scheduling table, and updates the residual cargo capacity of the logistics transport vehicle;
the path optimization unit acquires a transportation time attribute value and a transportation position attribute value of the logistics transport vehicle, compares the transportation position attribute value with a position value of the logistics transport homing site, and compares the transportation time attribute value with the length of the logistics transportation time sequence when the transportation position attribute value is not equal to the position value of the logistics transport homing site;
and when the transportation time attribute value is greater than or equal to the length of the logistics transportation time sequence, the path optimization unit moves the logistics transportation vehicle to the logistics transportation homing station, updates the transportation position attribute value of the logistics transportation vehicle to the position value of the logistics transportation homing station, and obtains the logistics transportation path of each logistics transportation vehicle according to the transportation scheduling table of each logistics transportation vehicle.
5. The system of claim 4, wherein the path optimization unit obtaining the transition probability of the logistics transportation vehicle from the current goods warehousing site to each of the other goods warehousing sites comprises:
the path optimization unit acquires a logistics transportation departure site and a logistics transportation arrival site of each cargo in the logistics transport vehicle, and acquires a cargo storage site passing through a space between the logistics transportation departure site and the logistics transportation arrival site of each cargo to obtain a site passing table of each cargo in the logistics transport vehicle;
the route optimization unit counts the occurrence frequency of each goods warehousing site according to the site route tables of all goods, and obtains the transfer coefficient from the current goods warehousing site to each other goods warehousing site according to the occurrence frequency of each goods warehousing site;
and the path optimization unit calculates the transfer probability from the current goods warehousing site to each other goods warehousing site according to the transfer coefficient from the current goods warehousing site to each other goods warehousing site.
6. The system of claim 5, wherein the transition probability is calculated by the formula
Wherein, PtTransition probability, R, for the t-th cargo storage sitetFor the transfer coefficient of the t-th cargo storage site, RkAnd (4) the transfer coefficient of the kth goods warehousing site, wherein k is the index of the goods warehousing site, and m is the number of the goods warehousing sites.
7. The system of claim 6, wherein the transportation schedule of the logistics transportation vehicle comprises cargo warehousing sites of all approaches of the logistics transportation vehicle; the logistics transportation path sequence comprises logistics transportation paths output by the same logistics transportation vehicle in each iteration process.
8. The system of claim 7, wherein the initializing unit discretizes the logistics transportation period according to the logistics update period to obtain the logistics transportation time sequence comprises:
T＝[T1,T2,T3…Tn]
△T＝Ti+1-Ti
t is logistics transportationTime sequence, Δ T is the logistics update period, TiFor the ith logistics transportation time point, Ti+1Is the (i + 1) th logistics transportation time point, and i is the index of the logistics transportation time point.
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| WO2023216560A1 (en) * | 2022-05-11 | 2023-11-16 | 弥费科技(上海)股份有限公司 | Path generation method and apparatus, computer device and storage medium |
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