CN108921353B

CN108921353B - Optimization method and device for yard distribution and electronic equipment

Info

Publication number: CN108921353B
Application number: CN201810738287.6A
Authority: CN
Inventors: 镇璐; 马成乐; 王凯
Original assignee: University of Shanghai for Science and Technology
Current assignee: University of Shanghai for Science and Technology
Priority date: 2018-07-06
Filing date: 2018-07-06
Publication date: 2021-12-07
Anticipated expiration: 2038-07-06
Also published as: CN108921353A

Abstract

The embodiment of the invention relates to the technical field of logistics, and discloses a vehicle distribution optimization method, a vehicle distribution optimization device and electronic equipment. The invention discloses a vehicle distribution optimization method, which comprises the following steps: determining a customer group required to be served by a train yard and a customer sequencing order in the customer group; adjusting the sequencing order of the clients in the client group; evaluating the adjusted client sorting sequence to determine a final client sorting sequence; determining a distribution scheme of the vehicles in the train yard according to the final customer sequencing sequence; and controlling the vehicle to transport according to the determined distribution scheme. And determining a reasonable yard distribution scheme by determining a customer group required to be served by the yard and adjusting and evaluating the determined final customer sorting sequence according to the initial customer sorting sequence. The vehicle is controlled to transport according to the determined yard distribution scheme, so that the yard transportation cost is reduced, and the transportation efficiency is improved.

Description

Optimization method and device for yard distribution and electronic equipment

Technical Field

The embodiment of the invention relates to the technical field of logistics, in particular to a method and a device for optimizing yard distribution and electronic equipment.

Background

With the rapid development of electronic commerce, the number of online shopping customers is larger and larger, so that the number of packages for logistics distribution is increased sharply, and higher requirements are put on the logistics service level. Customer complaints on online shopping are mainly focused on package delays and terminal delivery services. Therefore, the last mile allocation is very important for providing services to online shopping customers.

The inventor finds that at least the following problems exist in the prior art: when vehicles in a yard (distribution center) provide package distribution service for customers, the yard often does not have a reasonable transportation distribution scheme, which results in increased transportation cost and reduced transportation efficiency.

Disclosure of Invention

An object of an embodiment of the present invention is to provide a method, an apparatus, and an electronic device for optimizing yard delivery, which are capable of determining a customer group to be serviced by a yard, and determining a reasonable yard delivery scheme according to an initial customer sorting order, which is adjusted and evaluated to determine a final customer sorting order, thereby reducing the transportation cost of the yard and improving the transportation efficiency.

In order to solve the above technical problem, an embodiment of the present invention provides an optimization method for yard delivery, including the following steps:

determining a customer group required to be served by a train yard and a customer sequencing order in the customer group; adjusting the sequencing order of the clients in the client group; evaluating the adjusted client sorting sequence to determine a final client sorting sequence; determining a distribution scheme of the vehicles in the train yard according to the final customer sequencing sequence; and controlling the vehicle to transport according to the determined distribution scheme.

The embodiment of the invention also provides an optimization device for yard delivery, which comprises: the first determining module is used for determining a customer group required to be served by the train yard and a customer sequencing order in the customer group; the adjusting module is used for adjusting the sequencing order of the clients in the client group; the evaluation module is used for evaluating the adjusted client sorting sequence and determining the final client sorting sequence; the second determining module is used for determining a distribution scheme of the vehicles in the train according to the final customer sequencing sequence; and the transportation module is used for controlling the vehicle to transport according to the determined distribution scheme.

Embodiments of the present invention also provide an electronic device, comprising at least one processor; and a memory communicatively coupled to the at least one processor; the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the yard distribution optimization method.

The embodiment of the invention also provides a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to realize the optimization method for yard distribution.

Compared with the prior art, the method and the system for dispatching the train yard determine a reasonable train yard distribution scheme by determining the customer group required to be served by the train yard and adjusting and evaluating the determined final customer sorting sequence according to the initial customer sorting sequence. The vehicle is controlled to transport according to the determined yard distribution scheme, so that the yard transportation cost is reduced, and the transportation efficiency is improved.

In addition, the step of determining the customer group to be serviced by the train yard and the ordering order of the customers in the customer group comprises the following steps: and determining a customer group required to be served by the train yard by adopting a heuristic algorithm, and randomly generating a customer sequencing sequence in the customer group according to the customer group, wherein the heuristic algorithm comprises a genetic algorithm or a particle swarm algorithm. The client group which needs to be served by the departure yard can be quickly determined through a heuristic algorithm, and the client sorting sequence determined according to the determined client group is an initial sequence, so that a basis is provided for subsequently adjusting the client sorting sequence.

In addition, the heuristic algorithm is adopted to determine the customer groups to be served by the train yard and the ordering order of the customers in the customer groups, and comprises the following steps: encoding each customer; initializing each encoded client to obtain a respective random position value of each client; determining a customer group required to be served by the parking lot according to the respective random position value of each customer; and randomly generating a customer sorting order in the customer base according to the customer base.

In addition, the adjusting of the ordering order of the clients in the client group comprises: and adjusting the ordering sequence of the customers in the customer group by adopting a mobile, exchange or reversed variable neighborhood searching strategy. By adopting movement, transformation and inversion to carry out variable neighborhood search, the diversity of the customer sorting sequence adjustment method in the customer group is ensured.

In addition, evaluating the adjusted customer sorting order to determine a final customer sorting order, comprising: calculating the yard cost of the customer sorting sequence before adjustment and the yard cost of the customer sorting sequence after adjustment; judging whether the yard cost of the adjusted customer sorting sequence is less than the yard cost of the customer sorting sequence before adjustment, if so, taking the adjusted customer sorting sequence as the final customer sorting sequence, otherwise, taking the customer sorting sequence before adjustment as the final customer sorting sequence; wherein the yard cost comprises a vehicle journey cost, a time violation penalty cost and a capacity violation penalty cost. And evaluating the quality of the adjusted client sorting sequence by comparing the cost of the adjusted client sorting sequence with the cost of the client sorting sequence before adjustment, and determining the client sorting sequence with better quality as the final client sorting sequence according to the evaluation result.

Additionally, determining a delivery plan for the vehicles within the yard based on the final customer ranking includes determining a customer label based on the final customer ranking and determining a delivery plan for the vehicles within the yard based on the customer label.

In addition, the customer's tag includes: available time for the vehicle servicing the customer to travel the next trip, the customer's index of the previous customer, and the yard cost of transporting the vehicle in the yard to the customer.

Drawings

One or more embodiments are illustrated by way of example in the accompanying drawings, which correspond to the figures in which like reference numerals refer to similar elements and which are not to scale unless otherwise specified.

FIG. 1 is a flow chart of a method for optimizing yard delivery in a first embodiment of the present application;

FIG. 2 is a diagram illustrating a variable neighborhood search method according to a first embodiment of the present application;

FIG. 3 is a flow chart of a method for optimizing yard delivery in a second embodiment of the present application;

FIG. 4 is a block diagram of a yard distribution optimization apparatus according to a third embodiment of the present application;

FIG. 5 is a block diagram of an optimization device for yard distribution according to a fourth embodiment of the present application;

fig. 6 is a schematic structural diagram of an electronic device in a fifth embodiment of the present application.

Detailed Description

In order to make the objects, technical solutions and advantages of the embodiments of the present invention more apparent, embodiments of the present invention will be described in detail below with reference to the accompanying drawings. However, it will be appreciated by those of ordinary skill in the art that numerous technical details are set forth in order to provide a better understanding of the present application in various embodiments of the present invention. However, the technical solution claimed in the present application can be implemented without these technical details and various changes and modifications based on the following embodiments.

A first embodiment of the present invention relates to a method for optimizing yard delivery. The specific process is shown in fig. 1, and comprises the following steps:

step 101, determining a customer group to be serviced by a train yard and a customer sorting order in the customer group.

Specifically, in this embodiment, a heuristic algorithm may be used to determine a client group to be served in the train yard, and randomly generate a client sorting order in the client group according to the client group, where the heuristic algorithm in this embodiment includes a genetic algorithm or a particle swarm algorithm.

The customer group required to be served by the train yard is determined through a heuristic algorithm, each customer is coded, each coded customer is initialized to obtain a random position value of each customer, and the customer group required to be served by the train yard is determined according to the random position value of each customer.

In one specific implementation, a customer group required to be served by a parking lot is determined through a particle swarm algorithm, the number of customers is set to be N, and the number of parking lots is set to be D_kAnd N has a value of 10, D_kIs 2. Initializing the encoded customer, i.e. initializing the particle, by encoding each customer into a particle, determining a respective random position value for each customer by initializing the particle, and the random position value for each customer being a fraction between (0, 2). A list of random location values obtained after initialization for each client after encoding is shown in table 1.

TABLE 1

In this case, the customer group to be serviced by the yard is determined based on the respective random position value of each customer, for example, as can be seen from table 1, the random position values of customers {1, 2, 4, 5, 8} are distributed within [0, 1 ], and are thus assigned to be serviced by the yard {0 }. The random locations of the customers {0, 3, 6, 7} are distributed within [1, 2), so the allocation is served by the yard {1}, and the specific locations and specific names of the yard {0} and the yard {1} are known. Thus, for a determined yard {0}, the group of customers to be serviced by the yard can be determined as shown in table 2 below. And after the customer groups needing to be served by the parking lot {0} are determined, arranging the customer groups according to the sequence from small to large of the random position values of the customers in the customer groups, and determining the customer sequencing sequence in the customer groups, as shown in the following table 3.

It should be noted that the customer ranking order in the customer base determined according to the random position value is an initial order assigned to the customer base after the customer base to be served by the yard is determined, and the customer ranking order in the customer base can be adjusted on the basis of the initial order.

TABLE 2

1	2	4	5	8
					0.65	0.37	0.91	0.29	0.42

TABLE 3

5	2	8	1	4
					0.29	0.37	0.42	0.65	0.91

In the present embodiment, the customer group to be serviced by the yard may be specified by a genetic algorithm, but when the customer group to be serviced by the yard is specified by the genetic algorithm, each customer is encoded into a chromosome, the encoded customer is initialized, that is, the chromosome is initialized, and the random position value of each customer is specified by initializing the chromosome. And the random position value determined by initializing the chromosome through the genetic algorithm is a nonnegative integer when D_kWhen the value of (2) is obtained, the random position value of each client can only be 0 and 1. Determining the customer with the random position of 0, allocating the customer served by the parking lot {0}, and ordering the customers in the customer group in the parking lot {0} by following the order of the customer due to the fact that the value of the random position of the customer in the customer group allocated to the parking lot {0} service is 0Machine ordering to determine an initial order. The ordering order of the customers in the customer base can be adjusted on the basis of the initial order.

Step 102, adjusting the sequencing order of the clients in the client group.

Specifically, when the customer ranking order in the customer base is adjusted, the customer ranking order in the customer base can be adjusted respectively by using a mobile, exchange and reverse variable neighborhood search mode.

In one embodiment, after determining the customer base to be serviced in yard {0} and the initial customer ranking order {2, 1, 4, 5, 8}, as shown in FIG. 2, (a) is adjusted by move to indicate that the customer is relocated from one location to another location in the customer ranking order; (b) the position of the two clients is exchanged in the client sorting sequence for adjustment in an exchange mode; (c) to adjust in a reverse manner, the positions of a portion of consecutive customer sorting orders in the customer sorting order are shown reversed.

And 103, calculating the yard cost of the customer sorting sequence before adjustment and the yard cost of the customer sorting sequence after adjustment.

After the customer sorting order in the customer group is adjusted, the adjusted customer sorting order needs to be evaluated, and the specific mode is that the evaluation is carried out through the relationship between the yard cost of the customer sorting order before the adjustment and the yard cost of the customer sorting order after the adjustment.

It should be noted that, in a certain vehicle yard, delivery in a certain customer-ordered sequence may include a plurality of trips: assuming that d represents a yard, the customer ranking order determined in yard d is { a, b, c }, and the delivery is performed according to the determined customer ranking order, which may include multiple trips, if one trip is: d → a → b → c → d; there are two strokes respectively: d → a → b → d and d → c → d, or d → a → d and d → b → c → d; there are three strokes respectively: d → a → d, d → b → d and d → c → d. From the above description, it is known that the process of the vehicle starting from the yard and returning to the yard is counted as one trip. Moreover, one yard may include a plurality of vehicles, and in the distribution process of the yard, when the yard includes a plurality of trips, the plurality of trips may be completed by one vehicle or by a plurality of vehicles simultaneously. The specific number of vehicles in the vehicle yard is not limited in the embodiment of the application.

It should be noted that the yard cost includes a vehicle journey cost, a time violation penalty cost, and a capacity violation penalty cost. In a certain customer ranking order, the yard cost is shown in equation (1) below:

wherein S is_dRepresenting a determined customer ranking order in yard D, ρ representing the trip in yard D, D (ρ) representing the travel distance of trip ρ, TV (ρ) representing the amount of time violation in trip ρ, LV (ρ) representing the amount of load violation of the vehicle in trip ρ, W (ρ) representing the amount of load violation of the vehicle in trip ρ, and_drepresenting the number of all available trips in yard d. Q represents the upper limit of the load of the vehicle, theta represents a time penalty coefficient, lambda represents a vehicle load penalty coefficient, and theta and lambda can be automatically set manually according to actual conditions.

It should be noted that, if the determined customer sorting order before adjustment is W_d1The determined adjusted customer sorting order is W_d2Then the yard cost C (S) of the customer' S rank order before adjustment can be determined according to equation (1)_d1) And yard cost C (S) of the adjusted customer sequencing order_d2)。

And 104, judging whether the yard cost of the adjusted customer sorting sequence is less than the yard cost of the customer sorting sequence before adjustment, if so, executing the step 105, otherwise, executing the step 106.

And step 105, taking the adjusted client sorting sequence as a final client sorting sequence.

And step 106, taking the client sorting sequence before adjustment as the final client sorting sequence.

And step 107, determining a distribution scheme of the vehicles in the train according to the final customer sequencing order.

It should be noted that the labels of the customers are determined according to the final customer sorting order, and the distribution scheme of the vehicles in the train is determined according to the labels of the customers.

Wherein the label of the customer comprises: the available time for the vehicle serving the customer to travel the next trip, the index of the customer's previous customer, the yard cost of the vehicle in the yard as it is transported to the customer, the flag of whether the tag is obsolete, and the feasibility of the tag assignment scheme.

It should be noted that, because of yard distribution, each customer generates many tags in a customer-sorted order (except for the first customer which has only one tag). The labels of all clients are generated in sequence from the client at the first position in the client sorting sequence, but the label of the next client is generated only after the label of the previous client is generated and the 'dominated' label of the client is removed.

Wherein tags that are "dominated" will be discarded and therefore will not be generated based on the discarded tags when determining tags for subsequent customers in the customer ranking order. Therefore, the more tags that the front client is "dominated" in the client sorting order, the fewer tags that the rear client generates, and the faster the tag program can be calculated. In determining whether a tag is dominated, the tag is only compared to the rest of the tags under the same customer, and not to tags under other customers.

For example, with a label

And a label

For example, when the rule of tag governance is described and the formula (2) and the formula (3) are satisfied, the tag is determined

Domination label

γ≥1 (5)

Wherein,

presentation label

The cost of the yard of the vehicle,

label (R)

The cost of the yard of the vehicle,

presentation label

The (j) th element of (a),

presentation label

The yard cost of (a) and gamma represents a dynamic adjustment parameter for the number of tags of the customer.

And γ is updated according to equation (6), equation (6) being as follows:

wherein | v_iI represents the number of labels on the ith client in the client sorting order, upsilon_thrRepresenting a threshold parameter.

In one particular implementation, if the final customer ordering order is { c }₁,c₂,c₃Is assigned to a vehicle d, and there are in particular two vehicles k in the field d₀And k₁The upper limit of the vehicle load is 200, the maximum number of strokes per vehicle is 2, θ is 5, and λ is 5.

Customer information, first column number t, shown in Table 4^sRepresents the service time of the vehicle between the loading of the yard d and three customers; second column of numbers qⁱThe third column e shows the cargo demand (yard demand 0) of each customer_iIndicating the earliest starting service time of the time window (the yard starts from time 0), and the fourth column l_iRepresents the latest starting service time of the time window (the yard is 200); fifth column t^RA cargo ready time (0 is set when there is no cargo demand in the yard) indicating the cargo demanded by each customer; table 5 is a distance matrix between any two points; table 6 shows tag information of the customers determined according to the final customer ranking order, a first column time of each customer tag indicates available time for a vehicle serving the customer to travel the next trip and is ranked according to a numerical size in a non-ascending order, a second column P indicates an index of a customer previous to the customer, a third column cost indicates a yard cost when the vehicle in the yard is transported to the customer, a fourth column dom indicates whether the tag is deselected, and a fifth column fesi indicates feasibility of the tag assignment scheme.

TABLE 4

	t^s	qⁱ	e_i	l_i	t^R
						d	20	0	0	200	0
c₁	5	20	100	120	60
						c₂	5	20	50	100	20
c₃	5	20	130	160	60

TABLE 5

	d	c₁	c₂	c₃
					d	0	5	10	15
c ₁	5	0	10	20
					c₂	10	10	0	30
c₃	15	20	30	0

TABLE 6

It should be noted that, the label determination process of the client specifically includes generating corresponding labels according to the final client sorting order, and first generating c₁Then generates c₂Finally, generate c₃Tag of (c) below to generate c₁And c a label₂Is illustrated as an example because c₁The labels of (a) are generated on the basis of the yard d, c₂Is marked with a yard d and a customer c₁Generated on the basis of tags of c₃The labels of (1) are a parking lot d and a customer c₁Label and customer c₂Is generated as a basis, so c₃Principle of tag generation and c₂The label generation principle is the same, and the description is omitted here.

Wherein c is generated₁The labeling process comprises the following steps: the yard d is assigned a vehicle (not denoted as k)₀) Is c₁Delivery of goods and return to yard (each tag requiring return to yard) with only one trip, as shown in table 4, c₁Has a cargo demand of 20, a cargo ready time of 60, and a yard loading time of 20, so that k is₀The departure time from the yard was 80. From Table 4, the yards d to c₁Is 5, so k₀To c₁Is 85 (in the present embodiment, it is assumed that the travel time of 1 unit distance is also 1 unit). In Table 4, c₁Has a time window of [100, 120 ]]The term time window means that the vehicle must deliver the customer within the time range specified by the time window, so that the vehicleFor client c₁It is necessary to wait until 100 o' clock before unloading, the unloading time is 5, so k₀The vehicle is unloaded at time 105, starts to return to the yard, and arrives at yard d at time 110 after 5 units of time have elapsed. In this journey, there are no time window and no load violations.

Thus, in c₁In this tag, service c is represented₁The available time of the next trip of the vehicle is (110, 0), and the requirement of the sequence from large to small is met in the label, wherein the number group needs to be arranged in the sequence from large to small; then "P" column, let us see that this itinerary contains only client c₁Part of (1), i.e. { c₁The previous point is a parking lot d, and the value of the column P is recorded as d; then the "cost" for this trip is vehicle trip 10; for the first customer in the sequence, there is only one tag (delivery scenario, or vehicle routing) and therefore No other vehicle delivery scenario is preferred over the delivery scenario for the trip, and therefore the tag is not eliminated, the "dom" listing No; since there are no time violations and capacity violations, and thus this label assignment scheme is feasible, "fesi" is listed as Yes.

Wherein the first client point c in the sequence₁After the label is generated, a second customer point c is generated₂Tag of (2), generating c₂The labeling process comprises the following steps: as can be seen from Table 6, c₂With three labels, corresponding to three delivery schemes, the first being to arrange a vehicle for successive customers c in a journey₁And c₂Goods are delivered (since in this customer sequence c₁At c₂Before, therefore, in the same stroke, c is first given₁Service), and then returns to the yard (i.e., one vehicle runs one trip and another vehicle is not in use); in the second case, a vehicle is allocated and a journey c is first executed₁Delivering the goods and returning to the yard, c, during the second journey₂Delivering and returning to the yard (i.e. one vehicle runs for two times, and the other vehicle is not used); in a third case, a vehicle is assigned c₁Distributing and distributing another vehicle to c₂And (4) delivering, namely returning the two vehicles to the parking lot immediately after unloading (namely, running one trip for each vehicle).

For the first case, the sum of the quantities of the two customers is 15, no traffic load violation occurs, the maximum value of the ready time is 60, and c is generated₁Similar to the tag, vehicle has finished servicing at time 105 c₁But the next destination is c₂From Table 5, it can be seen that₁And c₂The distance between them is 10, so the vehicle passes 10 units of time and reaches c at 115₂But this time is later than c₂The latest service start time 100, so the time violation penalty cost is 5 x (115-; when this is said the vehicle is c₂The service start time is 100 (after a time window violation penalty, time is pulled back to the latest service start time of the time window), the cargo is unloaded after 5 units of time, the cargo is immediately returned to the yard at 105, and the cargo arrives at the yard at 115 after 10 units of time. While the other vehicle is not in use, the vehicle can prepare to travel the next trip, i.e. "time" column (115,0), which contains only part of the sequential customer, i.e. { c₁,c₂The previous point is a parking lot d, and the value of the column P is recorded as d; if the vehicle travel distance is 5+10+ 10-25, the vehicle trip cost "is listed as 25+ 75-100; the "dom" column is temporarily unknown and needs to be at c₂After all the tags are generated, whether the distribution scheme is better or not is judged, and whether the tags are eliminated or not can be determined; an infeasible scheme, due to the time violations, "fesi" column No;

for the second case, let a vehicle (not marked as k)₀) Two strokes of travel, due to the first stroke and c₁The unique tags are identical, so k₀A second trip may be prepared from time 110. Due to c₂Has a cargo ready time of 20, so k₀The cargo is loaded from the time 110, and the cargo arrives at the time c after 20 time units, that is, 10 time units from the departure of the yard d at the time 130 and the arrival of the cargo at the time 140₂Then the penalty cost for time violation is 5 × (140-; at this time, the service is started from the time 100, and passes5 units of time, starting to return to the yard at the time 105, and after 10 units of time, arriving at the yard at the time 115, the "time" column is (115, 0); comprises c₂C is the previous point of travel of₁Thus, the "P" column is denoted as c₁(ii) a The vehicle trip distance is 5 x 2+10 x 2-30, so the value in the "cost" column is 200+ 30-230. In calculating "dom", the tag is eliminated because it is greater than the cost of the first case, and the infeasible scheme "Fesi" is listed as No because of the time violation.

For the third case, note k₀Is c₁Service, k₁Is c₂Service, then k₀Correlation value of with c₁Are identical. For vehicle k₁，c₂Has a cargo ready time of 20, so k₁The loading is started at 20 hours, 20 units of time have elapsed, the vehicle departs from the yard at 40 hours, and 10 units of time have elapsed, i.e., 50 hours have reached c₂Due to c₂Has a time window of 50 earliest starting service time, so k₁Discharge was started at time 50, 5 units of time passed and left c at time 55₂Go to the yard and then arrive at the yard 10 units of time, i.e., time 65. There are no time violations and no capacity violations. "time" column is (110, 65); comprises c₂The previous point in the customer sequence is c₁Thus, the "P" column of the tag is c₁(ii) a "cost" is the sum of the yard costs of two vehicles when they are transported to the customer is 30, i.e. 5 x 2+10 x 2 is 30; since there is no violation, it is a feasible solution "fesi" to Yes. The "dom" column is then computed, and the tag is not eliminated because cost is less than the first case.

In the second case and the third case, the column "P" is c₁That is, the labels for the second case and the third case are based on c₁Of (c) of tag generation₁Only one unique tag), that is to say that the previously arranged scheme (k) is retained₀Is c₁Service and then return to yard) without modification and then add possible new ones laterArrangement (k)₀Run second trip service c₂Or using another vehicle service c₂)。

Wherein for c₃C, rules and the above₂The label generation process is the same, and is not described herein again. As shown in table 6, if two tags have the same minimum cost 60 and both are feasible, the first of them is selected and the distribution schedule for the vehicles in the yard is finally determined as: k is a radical of₀Execute two strokes { d → c₁→d，d→c₃→d}， k₁One run { d → c₂→d}。

And step 108, controlling the vehicle to transport according to the determined distribution scheme.

Wherein, after determining the distribution scheme of the vehicles in the yard according to the final customer sorting order, the yard is controlled to transport according to the determined distribution scheme.

For example, when the distribution scheme is determined as: k is a radical of₀Execute two strokes { d → c₁→d，d→c₃→d}，k₁One run { d → c₂→ d, the yard will control the vehicle k₀From the yard to customer c₁Delivery is carried out and the vehicle amount k is controlled₁For customer c₂Is distributed to the vehicles k₀After the first stroke is executed, the vehicle k is controlled₀From the yard to customer c₃And (6) carrying out distribution. Therefore, the distribution of the parking lot is more reasonable, the waste of parking lot transportation resources and the unreasonable distribution of time are avoided, and the transportation efficiency is improved.

Compared with the prior art, the method and the system determine a reasonable yard distribution scheme by determining the customer group required to be served by the yard and adjusting and evaluating the determined final customer sorting sequence according to the initial customer sorting sequence. The vehicle is controlled to transport according to the determined yard distribution scheme, so that the yard transportation cost is reduced, and the transportation efficiency is improved.

A second embodiment of the present invention relates to a method for optimizing yard delivery. The embodiment is further improved on the basis of the first embodiment, and the specific improvement is as follows: the adjustment of the ordering order of the clients in the client group is specifically described. The flow of the optimization method for yard delivery in this embodiment is shown in fig. 3. Specifically, in this embodiment, step 201 to step 210 are included, where step 201 is substantially the same as step 101 in the first embodiment, and step 205 to step 210 are substantially the same as step 103 to step 108 in the first embodiment, and are not described herein again, and differences are mainly introduced below, and technical details not described in detail in this embodiment may be referred to the substance detection method provided in the first embodiment, and are not described herein again.

After step 201, step 202 is performed.

In step 202, the ordering order of the clients in the client group is adjusted in a mobile manner.

It should be noted that, when determining the client group to be served by the yard and the initial client ordering order is the sequence a {2, 1, 4, 5, 8}, first trying to move from the client {2}, and the client {2} can move between {1} and {4}, between {4} and {5}, between {5} and {8} and {4}, then first putting it between {1} and {4}, the client sequence becomes the sequence B {1, 2, 4, 5, 8}, and determining whether the sequence B is better than the sequence a according to the evaluation criteria set by the user, if not, continuing to perform the next trying to move {2} between {4} and {5}, the sequence B becomes the sequence C {1, 4, 2, 5, 8}, and determining whether C is better than the sequence a according to the evaluation criteria set by the user, by analogy, if no better sequence is found by all movements of the first client {2}, the second client {1} is moved, and the position where the client {2} is movable is located before {2}, {4} and {5}, {5} and {8} and after {8}, if no new sequence in the client ordering order better than the a sequence is found by moving, step 203 is executed, and the adjustment is performed by exchanging.

In step 203, the customer sorting order in the customer group is adjusted by using an exchange method.

Specifically, when the client group to be serviced by the train yard and the initial client sorting order are determined to be the sequence a {2, 1, 4, 5, 8}, and when a better client sorting order cannot be found by mobile adjustment, adjustment is performed by exchanging positions of two clients in the client sorting order, first, the client {5} may be exchanged with the clients {2}, {8}, {1} and {4}, although there is an order same as the mobile manner by the exchange manner, the time used by the two transformations is different, and it is a factor to be considered when evaluating according to the evaluation criterion set by the user, so that evaluation results obtained by the transformation manner are different, and so on, if adjustment is performed by the exchange manner, according to the evaluation criterion set by the user, if no better sequence can be found, step 204 is executed to adjust by means of swapping.

In step 204, the ordering of the customers in the customer base is adjusted in a reverse manner.

Specifically, when the customer group to be served by the train yard and the initial customer sorting order are determined to be the sequence A {2, 1, 4, 5, 8} and when a better customer sorting order cannot be found by the exchange adjustment, the adjustment is performed in an inverse manner, that is, the positions of a part of continuous customer sorting orders in the customer sorting order are reversed. Wherein, in order to avoid the same exchange mode, at least three clients are included in a part of continuous client sorting sequence. When three clients are included in a portion of the client sequence, then {2, 1, 4}, {1, 4, 5}, {4, 5, 8} may be selected and reversed in sequence. Or when four clients are included in a portion of the client sequence, then {2, 1, 4, 5}, {1, 4, 5, 8} may be selected and reversed in sequence. And determining a group of comparison sequences which are better than the sequence A according to the evaluation standard set by the user, and if not, taking a group of sequences with the closest evaluation result as the adjusted customer sorting sequence.

The steps of the above methods are divided for clarity, and the implementation may be combined into one step or split some steps, and the steps are divided into multiple steps, so long as the same logical relationship is included, which are all within the protection scope of the present patent; it is within the scope of the patent to add insignificant modifications to the algorithms or processes or to introduce insignificant design changes to the core design without changing the algorithms or processes.

The third embodiment of the invention relates to an optimization device for yard distribution, and the specific structure is as shown in fig. 4.

As shown in fig. 4, the optimization apparatus for yard distribution includes: a first determination module 301, an adjustment module 302, an evaluation module 303, a second determination module 304, and a transportation module 305.

The first determining module 301 is configured to determine a customer group to be serviced by the yard and a customer sorting order in the customer group.

And an adjusting module 302, configured to adjust a client sorting order in the client group.

And the evaluation module 303 is configured to evaluate the adjusted client sorting order to determine a final client sorting order.

A second determination module 304 for determining a delivery schedule for the vehicles within the yard based on the final customer ranking order.

And a transportation module 305 for controlling the vehicle to transport according to the determined delivery scheme.

It should be understood that this embodiment is an example of the apparatus corresponding to the first embodiment, and may be implemented in cooperation with the first embodiment. The related technical details mentioned in the first embodiment are still valid in this embodiment, and are not described herein again in order to reduce repetition. Accordingly, the related-art details mentioned in the present embodiment can also be applied to the first embodiment.

A fourth embodiment of the present invention relates to an optimization device for yard delivery. This embodiment is substantially the same as the third embodiment, and the specific configuration is as shown in fig. 5. Wherein, the main improvement lies in: the fourth embodiment specifically describes the structure of the adjustment module 302 in the third embodiment.

Wherein, the adjusting module 302 comprises: a move trim sub-module 3021, a swap trim sub-module 3022, and a reverse trim sub-module 3023.

And the moving adjusting submodule 3021 is configured to adjust the client sorting order in the client group in a moving manner.

And the switching adjustment submodule 3022 is configured to adjust the client sorting order in the client group in a switching manner.

And an inverse adjustment submodule 3023 configured to adjust the ordering order of the clients in the client group in an inverse manner.

It should be understood that this embodiment is an example of the apparatus corresponding to the second embodiment, and that this embodiment can be implemented in cooperation with the second embodiment. The related technical details mentioned in the second embodiment are still valid in this embodiment, and are not described herein again in order to reduce repetition. Accordingly, the related-art details mentioned in the present embodiment can also be applied to the second embodiment.

It should be noted that each module referred to in this embodiment is a logical module, and in practical applications, one logical unit may be one physical unit, may be a part of one physical unit, and may be implemented by a combination of multiple physical units. In addition, in order to highlight the innovative part of the present invention, elements that are not so closely related to solving the technical problems proposed by the present invention are not introduced in the present embodiment, but this does not indicate that other elements are not present in the present embodiment.

A fifth embodiment of the present invention relates to an electronic device, as shown in fig. 6, including at least one processor 501; and a memory 502 communicatively coupled to the at least one processor 501; the memory 502 stores instructions executable by the at least one processor 501, and the instructions are executed by the at least one processor 501, so that the at least one processor 501 can perform the optimization method for yard delivery in the above embodiments.

In this embodiment, the processor 501 is a Central Processing Unit (CPU), and the Memory 502 is a Random Access Memory (RAM). The processor 501 and the memory 502 may be connected by a bus or other means, and fig. 6 illustrates the connection by the bus as an example. The memory 502 is a non-volatile computer-readable storage medium that can be used to store non-volatile software programs, non-volatile computer-executable programs, and modules, such as the programs that implement the environment information determination method in the embodiments of the present application, in the memory 502. The processor 501 executes various functional applications of the device and data processing by running nonvolatile software programs, instructions, and modules stored in the memory 502, that is, the optimization method for the yard distribution described above is implemented.

The memory 502 may include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store a list of options, etc. Further, the memory may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid state storage device. In some embodiments, memory 502 may optionally include memory located remotely from processor 501, which may be connected to an external device via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.

One or more program modules are stored in the memory 502 and, when executed by the one or more processors 501, perform the yard delivery optimization method of any of the method embodiments described above.

The product can execute the method provided by the embodiment of the application, has corresponding functional modules and beneficial effects of the execution method, and can refer to the method provided by the embodiment of the application without detailed technical details in the embodiment.

A sixth embodiment of the present application relates to a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, is capable of implementing a method for optimizing yard delivery as referred to in any of the method embodiments of the present invention.

Those skilled in the art will understand that all or part of the steps in the method according to the above embodiments may be implemented by a program instructing related hardware to complete, where the program is stored in a storage medium and includes several instructions to enable a device (which may be a single chip, a chip, etc.) or a processor (processor) to execute all or part of the steps in the method according to the embodiments of the present application. 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.

It will be understood by those of ordinary skill in the art that the foregoing embodiments are specific examples for carrying out the invention, and that various changes in form and details may be made therein without departing from the spirit and scope of the invention in practice.

Claims

1. A method for optimizing yard distribution, comprising:

determining a customer group required to be serviced by a train yard and a customer sequencing order in the customer group;

adjusting the ordering order of the clients in the client group;

evaluating the adjusted client sorting sequence to determine a final client sorting sequence;

determining a delivery scheme for vehicles within the yard according to the final customer ranking order;

controlling the vehicle to transport according to the determined distribution scheme;

wherein the evaluating the adjusted customer sorting order to determine a final customer sorting order comprises: calculating the yard cost of the customer sorting sequence before adjustment and the yard cost of the customer sorting sequence after adjustment; judging whether the yard cost of the adjusted customer sorting sequence is less than the yard cost of the customer sorting sequence before adjustment, if so, taking the adjusted customer sorting sequence as the final customer sorting sequence, otherwise, taking the customer sorting sequence before adjustment as the final customer sorting sequence; wherein the yard cost comprises a vehicle journey cost, a time violation penalty cost and a capacity violation penalty cost;

the determining a delivery schedule for the in-vehicle based on the final customer-ordered sequence includes: determining the labels of the customers according to the final customer sorting sequence, and determining the distribution scheme of the vehicles in the train according to the labels of the customers;

wherein the customer's tag comprises: available time for a vehicle servicing the customer to travel a next trip, an index of a customer previous to the customer, the yard cost when vehicles in the yard are transported to the customer, a flag of whether tags are obsolete, and feasibility of a tag assignment scheme.

2. The method of claim 1, wherein the determining a group of customers to be serviced by the yard and an order of ordering of the customers in the group of customers comprises:

and determining a customer group required to be served by the train yard by adopting a heuristic algorithm, and randomly generating a customer sequencing sequence in the customer group according to the customer group, wherein the heuristic algorithm comprises a genetic algorithm or a particle swarm algorithm.

3. The optimization method for yard distribution according to claim 2, wherein said determining the customer group to be serviced by the yard and the ordering order of the customers in the customer group by using a heuristic algorithm comprises:

encoding each customer;

initializing each encoded client to obtain a respective random position value of each client;

determining a customer group required to be served by the parking lot according to the respective random position value of each customer;

and determining the customer sorting order in the customer group according to the random position value of the customers in the customer group.

4. The method of claim 3, wherein said adjusting the customer ranking order in said customer base comprises:

and adjusting the ordering sequence of the customers in the customer group by adopting a mobile, exchange or reversed variable neighborhood searching strategy.

5. An optimization device for yard distribution, comprising:

the system comprises a first determining module, a second determining module and a control module, wherein the first determining module is used for determining a customer group required to be served by a train yard and a customer sequencing order in the customer group;

the adjusting module is used for adjusting the sequencing order of the clients in the client group;

the evaluation module is used for evaluating the adjusted client sorting sequence and determining the final client sorting sequence, and comprises: calculating the yard cost of the customer sorting sequence before adjustment and the yard cost of the customer sorting sequence after adjustment; judging whether the yard cost of the adjusted customer sorting sequence is less than the yard cost of the customer sorting sequence before adjustment, if so, taking the adjusted customer sorting sequence as the final customer sorting sequence, otherwise, taking the customer sorting sequence before adjustment as the final customer sorting sequence; wherein the yard cost comprises a vehicle journey cost, a time violation penalty cost and a capacity violation penalty cost;

a second determination module for determining a delivery schedule for vehicles within the yard based on the final customer ranking order, comprising: determining the labels of the customers according to the final customer sorting sequence, and determining the distribution scheme of the vehicles in the train according to the labels of the customers; wherein the customer's tag comprises: available time for a vehicle servicing the customer to travel a next trip, an index of a customer previous to the customer, the yard cost when vehicles in the yard are transported to the customer, a flag of whether tags are obsolete, and feasibility of a tag assignment scheme;

and the transportation module is used for controlling the vehicle to transport according to the determined distribution scheme.

6. An electronic device, comprising

At least one processor; and the number of the first and second groups,

a memory communicatively coupled to the at least one processor; wherein,

the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the yard distribution optimization method of any one of claims 1 to 4.

7. A computer-readable storage medium, in which a computer program is stored, which, when being executed by a processor, carries out a method for optimizing yard delivery according to any one of claims 1 to 4.