CN113469417B - Express vehicle transportation scheduling method, system and equipment - Google Patents

Express vehicle transportation scheduling method, system and equipment Download PDF

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CN113469417B
CN113469417B CN202110649388.8A CN202110649388A CN113469417B CN 113469417 B CN113469417 B CN 113469417B CN 202110649388 A CN202110649388 A CN 202110649388A CN 113469417 B CN113469417 B CN 113469417B
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孟凡超
王蕾
初佃辉
周学权
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Abstract

The express vehicle transportation scheduling method, system and equipment provided by the invention realize uniform vehicle scheduling, effectively reduce the number of vehicles actually used, reduce transportation distance and achieve the purpose of reducing transportation cost. Firstly, acquiring a regional transfer center set and constructing a vehicle transportation network diagram; then, acquiring relevant information of clearing of an enterprise transfer center, entering and leaving port express mails and network point vehicles, and analyzing main information of the express mails and transport vehicles; on the basis, a vehicle optimization scheduling model of a sharing network point is established, and an optimization target and constraint conditions are determined; and finally, adopting a two-stage algorithm to carry out vehicle scheduling. The invention can orient the optimized dispatching of vehicles of the shared network to the transfer centers of the express enterprises, and formulate a uniform vehicle transportation scheme for the tasks of entering and leaving ports of each transfer center.

Description

Express vehicle transportation scheduling method, system and equipment
Technical Field
The invention relates to the technical field of intelligent logistics, in particular to a method, a system and equipment for express vehicle transportation scheduling.
Background
In express city distribution, each express enterprise builds a transit center operated by itself in a city, the express firstly arrives at the city transit center for sorting, and after sorting is finished, the subordinate franchise network points automatically go to the center to take away the goods express, and then the goods express is distributed to customer masses from the terminal franchise network points. During the taking process, the express to be sent is sent to the center along with the express to be sent on the previous day. According to the existing transportation mode of single main body of transportation, after the joint distribution and integration are carried out, the franchising network points are integrated to the sharing network points, the number of members entering the port is doubled, and the sharing network points need to send goods vehicles to the transit centers of enterprises every day. According to the scale of the parts, one or more times of round trip can be carried out, and the condition that the loading is not full exists in the last round of freight car, so that the transportation resources are seriously wasted by the end goods. The mismatching of the vehicle and the goods causes serious resource waste, the utilization rate of the vehicle resources is low, and the transportation cost is high.
In a network of a shared network point and a plurality of express company transfer centers, under the condition of known traffic, the goods taking and delivery are considered at the same time, the central goods quantity is reasonably split, and a proper dispatching route is planned. When all the traffic is completed within the time limit, the number of vehicles actually used is effectively reduced, the transportation distance is reduced, and the purpose of reducing the transportation cost is achieved. How to reasonably split the central part amount and plan a proper transportation scheduling route is a problem to be solved currently.
There is less theoretical research on the application of practical constraints in split-optimal scheduling. The research of the existing model mainly considers the demand to be continuously split or arbitrarily split according to units, the assumption has certain limitation, the demand of customers in actual transportation can not be split in units frequently, and the model can not be applied to actual scenes with different package weights of logistics express. Meanwhile, the related research considering the time window is less, the application scenes are mostly simulation examples or simulation cases with smaller scale, and the difference from the actual application is larger.
Disclosure of Invention
Aiming at the problems in the prior art, the invention aims to provide an express delivery vehicle transportation scheduling method, system and equipment, aiming at the problem of transportation and goods taking from a transportation center to a sharing network point in express logistics, the independent transportation to the transportation center of each express delivery company for goods taking has vehicle redundancy, the empty load rate of tail goods is very high, and the transportation cost is increased. By applying a common delivery mode, a shared network point vehicle optimization scheduling model is established, a two-stage algorithm is used for solving, the planning timeliness is effectively guaranteed, and the common delivery of goods-taking trucks is realized.
In order to achieve the purpose, the invention is realized by the following technical scheme:
an express delivery vehicle transportation scheduling method comprises the following steps:
s1: acquiring a regional transfer center set, and constructing a vehicle transportation network diagram;
s2: establishing an entry and exit express task set and a transport vehicle set according to the clearing information of a transfer center of an express company;
s3: establishing a sharing network point vehicle optimization scheduling model, and determining an optimization target and constraint conditions;
s4: configuring an express item combination strategy based on descending order first-time adaptation;
s5: configuring a two-stage algorithm based on comprehensive priority;
s6: and based on the descending order first-time adaptive express item combination strategy, a two-stage algorithm based on comprehensive priority is adopted for vehicle scheduling.
Further, step S1 includes:
a vehicle co-operation network is defined using (V, E) where V ═ {0,1,2, …, n } ═ V 0 ∪V 1 Is a set of nodes, V 0 0 is a shared dot, V 1 N is a set of transit centers, and n is the number of transit centers; e { (i, j) | (i, j) ∈ V } is an edge set between nodes, each edge (i, j) ∈ E represents an optimal route from the node i to the node j, and d ij Representing the distance of the edge (i, j) which satisfies the symmetry, i.e., d ij ＝d ji The distance between the same nodes being 0, i.e. d ii ＝0，i∈V。
Further, the step S2 includes the following steps:
s2.1: let P be { P ═ P 1 ,p 2 ,…,p n Is the set of all the taken quantities of each transit center in a certain period, p i Taking the quantity of the workpieces at a transfer center i; let D ═ D 1 ,d 2 ,…,d n D is the set of all delivered quantities of each transfer center in a certain period of time i The quantity of the delivered parts at the transfer center i; for each transit centre i, t i Is the latest pick-up time of the pick-up task i, c i (t i ) For a time penalty cost according to the rules of a hard time window, c i For a great time penalty cost, the pickup time of the vehicle must be t i Within time, if late, then receive a time penalty c i ＝c(t-t i )；
S2.2: let K be { K ═ K 1 ,k 2 ,…,k v Is the set of available vehicles, where v is the number of vehicles, l k Is the maximum load capacity, s, of the vehicle k k And the average running speed of the vehicle k is shown, the vehicle belongs to the sharing network point, starts from the sharing network point and finally returns to the sharing network point.
Further, the step S3 includes:
use of
Figure BDA0003110482400000034
Indicating whether the vehicle k is traveling directly from point i to point j, where,
Figure BDA0003110482400000035
k is K, i is V, j is V, and if so, then
Figure BDA0003110482400000036
Otherwise
Figure BDA0003110482400000037
Using y i,k The method comprises the following steps of (1) representing that a vehicle K fully takes a part from a transfer center i, wherein K belongs to K, i belongs to V;
using z i,k The method comprises the following steps of (1) representing that a vehicle K fully sends a part to a transfer center i, wherein K belongs to K, i belongs to V;
using u i,k Indicates whether the vehicle k reaches a point i, where u i,k E {0,1}, K e K, i e V, if vehicle K reaches point i, then u is a i,k 1, otherwise u i,k ＝0；
Establishing a sharing network point vehicle optimization scheduling model, which specifically comprises the following formula:
Figure BDA0003110482400000031
Figure BDA0003110482400000032
wherein the constraint condition comprises the following formula:
Figure BDA0003110482400000033
Figure BDA0003110482400000041
Figure BDA0003110482400000042
Figure BDA0003110482400000043
Figure BDA0003110482400000044
Figure BDA0003110482400000045
Figure BDA0003110482400000046
Figure BDA0003110482400000047
Figure BDA0003110482400000048
Figure BDA0003110482400000049
u i，k ∈{0，1}i∈V，k∈K (13)
in the vehicle optimized dispatching model of the sharing network point, a formula (1) is an optimized objective function of the model and represents that the total transportation path of all vehicles is minimized, and a formula (2) is an optimized objective function of the model and represents that the transportation time cost of all vehicles is minimized; the formula (3) and the formula (4) represent the load constraint of the vehicle, and represent that the total weight of all express items of each pick-up and delivery can not exceed the maximum load of the delivery vehicle; formulas (5) and (6) show that the task of taking and sending the workpieces of each transfer center can be met; formulas (7) and (8) represent the distribution path constraint of the transfer center, and the vehicle only passes through the center of the picked and delivered goods once in each vehicle transportation task; the formula (9) and the formula (10) show that the quantity of the workpieces taken and sent by any vehicle to the transfer center cannot exceed the total task quantity of the center; equation (11) represents vehicle end point constraints, with vehicles returning to the end shared dot 0 after each task group is complete; the formula (12) and the formula (13) are defined for decision variables.
Further, the express mail combination strategy based on descending order first-time adaptation comprises the following specific steps:
s4.1: inputting express mail set t ═ t 1 ,t 2 ,...,t n }；
S4.2: express item t for set t i The cargo quantities are arranged in descending order;
s4.3: judging whether all the express items are reasonably combined, if all the express items are combined, turning to the step S4.7, otherwise, turning to the step S4.4;
s4.4: setting the package count m to be 0, the package size to be the current combination grade, and the current package to be B 1 ,B 2 ,...,B m ；
S4.5: in B 1 ,B 2 ,...,B m Searching for the current express t i Loading the first package, and if the first package cannot be loaded, opening a new package;
s4.6: judging whether all the parcels meet the grade requirement of 90 percent of standard amount, if so, turning to the step S4.7, otherwise, releasing the parcel B j The express item in the package is in the set t, the rest packages are stored, and the step S4.2 is carried out;
s4.7: and storing the combined parcel set B, and finishing the express item combination strategy based on descending order first-time adaptation.
Further, step S5 specifically includes the following steps:
s5.1: input parcel set B ═ B 1 ,b 2 ,...,b n }；
S5.2: selecting the packages with the grade of one grade in the packages B, and distributing vehicles by the transfer centers to which the packages with the grade of one grade belong;
s5.3: judging whether the vehicle only loads a single primary package, releasing the vehicle, recording the condition of completely loading the vehicle to a result set, and deleting the loaded primary package in the step B;
s5.4: starting from the current node v, calculating the priority of other nodes by integrating the time window and the distance, and arranging the priority in a descending order;
s5.5: selecting a node v ' with the highest priority, loading the rest packages in the node v ' in a descending order according to the weight, if the volume of the packages exceeds the capacity of the vehicles, recording the packages to a result set, distributing new vehicles, keeping the vehicles k to the next node if the remaining space still exists, and updating the v as v ';
s5.6: judging whether all central nodes are loaded, if so, executing a step S5.7, otherwise, executing a step S5.4;
s5.7: selecting non-primary parcel vehicle records in a result set, and performing shortest path planning on nodes passing through in the vehicles;
s5.8: judging whether all multi-node vehicle paths in the result set are optimized, if so, executing the step
S5.9, otherwise, executing the step S5.7;
s5.9: and (5) finishing the algorithm and outputting a scheduling result.
Further, the method is simple. Step S6 specifically includes the following steps:
s6.1: initializing an express item set t, a vehicle set K and a node set V;
s6.2: arranging all the express items in the express item set t in a descending order according to the express item weight;
s6.3: applying a descending order first-adapted express item combination strategy to package express items, and obtaining a package set B;
s6.4: loading the primary packages of each transfer center in the package set B independently;
s6.5: obtaining a residual package set B';
s6.6: judging whether all the transfer centers are loaded, if so, executing a step S6.9, otherwise, executing a step S6.7;
s6.7: arranging the transfer centers according to the comprehensive priority;
s6.8: loading the packages in descending order according to the package cargo quantity, and going to the step S6.6;
s6.9: recording the distributed vehicle results to a result set;
s6.10: judging whether all vehicles are optimized, if so, executing a step S6.12, otherwise, executing a step S6.11;
s6.11: planning the shortest path of the nodes passed by the vehicle, and turning to the step S6.10;
s6.12: and reading the result set and outputting the optimal solution.
Correspondingly, the invention also discloses an express delivery vehicle transportation scheduling system, which comprises:
the composition unit is used for acquiring a regional transfer center set and constructing a vehicle transportation network diagram;
the system comprises a set building unit, a transport vehicle set and a control unit, wherein the set building unit is used for building an entry port express item task set, an exit port express item task set and a transport vehicle set according to express company transfer center clearing information;
the model building unit is used for building a vehicle optimization scheduling model of a sharing network point and determining an optimization target and a constraint condition;
the strategy configuration unit is used for configuring an express item combination strategy which is firstly adapted based on descending order;
the algorithm configuration unit is used for configuring a two-stage algorithm based on the comprehensive priority;
and the calculating unit is used for scheduling the vehicles by adopting a two-stage algorithm based on comprehensive priority based on the descending order first-adapted express item combination strategy.
Correspondingly, the invention also discloses express vehicle transportation and dispatching equipment, which comprises:
a memory for storing a computer program;
a processor for implementing the express vehicle transportation scheduling method steps as described in any of the above when executing the computer program.
Compared with the prior art, the invention has the beneficial effects that: the invention provides a method, a system and equipment for transporting and scheduling express delivery vehicles, which are used for solving the problem of picking up goods by an express delivery flow facing a plurality of express delivery enterprise transit centers after integration of shared network points, providing a shared network point vehicle resource optimization scheduling model by considering the common delivery of one vehicle to the plurality of enterprise centers, and designing a two-stage algorithm based on a combination strategy. The distribution network of the sharing network after transverse cooperation is adopted to carry out intensive and intelligent transportation, so that the transport capacity resources of a plurality of enterprises are utilized in a centralized manner, the actual load rate of the distribution transport capacity is improved, vehicles on the road can be effectively reduced, and cross transportation and repeated route transportation can be reduced.
The invention realizes the purpose of effectively reducing the number of vehicles actually used, reducing the transportation distance and reducing the transportation cost by unified vehicle scheduling. Specifically, the method comprises the following steps: firstly, acquiring a regional transfer center set and constructing a vehicle transportation network diagram; then, acquiring relevant information of clearing of an enterprise transfer center, entering and leaving port express mails and network point vehicles, and analyzing main information of the express mails and transport vehicles; on the basis, a vehicle optimization scheduling model of a sharing network point is established, and an optimization target and constraint conditions are determined; and finally, adopting a two-stage algorithm based on a combination strategy to carry out vehicle scheduling. The vehicle optimized dispatching model of the sharing network point can be used for orienting the vehicle optimized dispatching of the sharing network point to the transportation centers of the express enterprises and formulating a uniform vehicle transportation scheme for the tasks of entering and leaving ports of each transportation center.
Therefore, compared with the prior art, the invention has prominent substantive features and remarkable progress, and the beneficial effects of the implementation are also obvious.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the provided drawings without creative efforts.
FIG. 1 is a flow chart of the method of the present invention;
FIG. 2 is a schematic illustration of a shared dot vehicle co-operation schedule within an area of the present invention;
FIG. 3 is a flow chart of the present invention for a descending order based first-time adaptation combining strategy;
FIG. 4 is a flow chart of a two-stage algorithm of the present invention based on integrated priority;
FIG. 5 is a flow chart of the combined strategy two-stage algorithm solution of the present invention;
fig. 6 is a system configuration diagram of the present invention.
In the figure, 1 is a composition unit, 2 is a set building unit, 3 is a model building unit, 4 is a strategy configuration unit, 5 is an algorithm configuration unit, and 6 is a calculation unit.
Detailed Description
The following description of the embodiments of the present invention will be made with reference to the accompanying drawings.
As shown in fig. 1, the express delivery vehicle transportation scheduling method includes the following steps:
s1: and acquiring a regional transfer center set, and constructing a vehicle transportation network diagram.
The vehicle-sharing network may be defined by the graph G ═ (V, E), where V ═ {0,1,2, …, n } ═ V 0 ∪V 1 Is a set of nodes, V 0 0 is a shared dot, V 1 N is a set of transit centers, and n is the number of transit centers; e { (i, j) | (i, j) ∈ V } is an edge set between nodes, each edge (i, j) ∈ E represents an optimal route from the node i to the node j, and d ij Representing the distance of the edge (i, j) which satisfies the symmetry, i.e., d ij ＝d ji The distance between the same nodes is 0, i.e. d ii ＝0，i∈V。
S2: and establishing an entry and exit express task set and a transport vehicle set according to the clearing information of the transfer center of the express company.
The method specifically comprises the following steps:
s2.1: let P be { P } 1 ,p 2 ,…,p n Is the set of all the taken quantities of each transit center in a certain period, p i Taking the quantity of the workpieces at a transfer center i; let D ═ D 1 ,d 2 ,…,d n Is a certainA set of all delivered quantities at each transfer centre in a period of time, d i The quantity of the delivered parts at the transfer center i; for each transit centre i, t i Is the latest pick-up time of the pick-up task i, c i (t i ) For a time penalty cost according to the rules of a hard time window, c i For a great time penalty cost, the pickup time of the vehicle must be t i Within time, if late, then receive a time penalty c i ＝c(t-t i )。
S2.2: let K be K ═ K 1 ,k 2 ,…,k v Is the set of available vehicles, where v is the number of vehicles, l k Is the maximum load capacity, s, of the vehicle k k And the average running speed of the vehicle k is shown, the vehicle belongs to the sharing network point, starts from the sharing network point and finally returns to the sharing network point.
Fig. 2 depicts a schematic view of a shared network point vehicle transportation schedule in an area. The region is provided with 1 shared network point shared by multiple franchises and 5 express enterprise transfer centers (A, B, C, D, E), wherein each transfer center is respectively provided with a certain quantity of outgoing parts and incoming parts, a single-body transportation route and a shared transportation schedule which are not planned by a transportation schedule are adopted, and the incoming parts of the transfer centers C and D are respectively split into (C) 1 ,C 2 ) And (D) 1 ,D 2 ) Two freight vehicles enter the port to take the goods so as to complete the overall task. The number of vehicles used is effectively reduced from 5 to 3.
S3: and establishing a vehicle optimized dispatching model of a sharing network point, and determining an optimized target and a constraint condition.
The method comprises the following specific steps:
use of
Figure BDA0003110482400000101
Indicating whether the vehicle k is traveling directly from point i to point j, where,
Figure BDA0003110482400000102
k is K, i is V, j is V, and if so, then
Figure BDA0003110482400000103
Otherwise
Figure BDA0003110482400000104
Using y i,k The method comprises the following steps of (1) representing that a vehicle K fully takes a part from a transfer center i, wherein K belongs to K, i belongs to V;
using z i,k The method comprises the following steps of (1) representing that a vehicle K fully sends a part to a transfer center i, wherein K belongs to K, i belongs to V;
using u i,k Indicates whether the vehicle k reaches a point i, where u i,k E {0,1}, K e K, i e V, if vehicle K reaches point i, then u is a i,k 1, otherwise u i,k ＝0；
Establishing a sharing network point vehicle optimization scheduling model, which specifically comprises the following formula:
Figure BDA0003110482400000105
Figure BDA0003110482400000106
wherein the constraint condition comprises the following formula:
Figure BDA0003110482400000107
Figure BDA0003110482400000108
Figure BDA0003110482400000109
Figure BDA00031104824000001010
Figure BDA00031104824000001011
Figure BDA00031104824000001012
Figure BDA00031104824000001013
Figure BDA0003110482400000111
Figure BDA0003110482400000112
Figure BDA0003110482400000113
u i,k ∈{0,1}i∈V,k∈K (13)
in the vehicle optimized dispatching model of the sharing network point, a formula (1) is an optimized objective function of the model and represents that the total transportation path of all vehicles is minimized, and a formula (2) is an optimized objective function of the model and represents that the transportation time cost of all vehicles is minimized; the formula (3) and the formula (4) represent the load constraint of the vehicle, and represent that the total weight of all express items of each pick-up and delivery can not exceed the maximum load of the delivery vehicle; formulas (5) and (6) show that the task of taking and sending the workpieces of each transfer center can be met; formulas (7) and (8) represent the distribution path constraint of the transfer center, and the vehicle only passes through the center of the picked and delivered goods once in each vehicle transportation task; the formulas (9) and (10) show that the quantity of the taken and sent parts of any vehicle to the transfer center cannot exceed the total task quantity of the center; equation (11) represents vehicle end point constraints, with vehicles returning to the end shared dot 0 after each task group is complete; the formula (12) and the formula (13) are defined for decision variables.
S4: and configuring an express item combination strategy which is firstly adapted based on descending order.
As shown in fig. 3, the express mail combination strategy based on descending order first adaptation in this step includes the following specific steps:
s4.1: inputting express mail set t ═ t 1 ,t 2 ,...,t n }。
S4.2: express item t for set t i The cargo quantities are arranged in descending order.
S4.3: and judging whether all the express items are reasonably combined, if all the express items are combined, turning to the step S4.7, and if not, turning to the step S4.4.
S4.4: setting the package count m to be 0, the package size to be the current combination grade, and the current package to be B 1 ,B 2 ,...,B m 。
S4.5: in B 1 ,B 2 ,...,B m Searching for the current express item t i And loading, and if not, opening a new package.
S4.6: judging whether all the parcels meet the grade requirement of 90 percent of standard amount, if so, turning to the step S4.7, otherwise, releasing the parcel B j And (5) storing the other packages when the express item in the package is in the set t, and turning to the step S4.2.
S4.7: and storing the combined parcel set B, and finishing the express item combination strategy based on descending order first-time adaptation.
S5: and configuring a two-stage algorithm based on the comprehensive priority.
As shown in fig. 4, the flow of the two-stage algorithm based on the comprehensive priority specifically includes the following steps:
s5.1: input parcel set B ═ B 1 ,b 2 ,...,b n }。
S5.2: and selecting the packages with the grade of one in the packages B, and distributing the vehicles by the transfer centers to which the packages of the grade one belong.
S5.3: and judging whether the vehicle only loads a single primary package, releasing the vehicle, recording the condition of completely loading the vehicle to result, and deleting the loaded primary package in the step B.
S5.4: and starting from the current node v, calculating the priority of the other nodes by integrating the time window and the distance, and arranging the priority in a descending order.
S5.5: and selecting a node v ' with the highest priority, loading the rest packages in the node v ' in a descending order according to the weight, if the volume of the packages exceeds the capacity of the vehicles, recording the packages to a result, distributing a new vehicle, keeping the vehicle k to the next node if the remaining space still exists, and updating the v to be v '.
S5.6: and (4) judging whether all the central nodes are loaded or not, if so, executing the step S5.7, and otherwise, executing the step S5.4.
S5.7: and selecting non-primary package vehicle records in the result, and performing shortest path planning on nodes passing through in the vehicle.
S5.8: and judging whether all multi-node vehicle paths of result are optimized, if so, executing the step S5.9, and otherwise, executing the step S5.7.
S5.9: and (5) finishing the algorithm and outputting a scheduling result.
S6: and based on the descending order first-time adaptive express item combination strategy, a two-stage algorithm based on comprehensive priority is adopted for vehicle scheduling.
As shown in fig. 5, the two-stage algorithm flow of the first-time adapted express mail combination strategy based on descending order includes the following steps:
s6.1: and initializing an express item set t, a vehicle set K and a node set V.
S6.2: and arranging all the express items in the express item set t in descending order of the express item weight.
S6.3: and applying the express item combination strategy which is firstly adapted in descending order to package express items, and obtaining a package set B.
S6.4: and (4) carrying out independent loading on the primary packages of each transfer center in the package set B.
S6.5: the remaining parcel set B' is obtained.
S6.6: and (4) judging whether all the transfer centers are loaded, if so, executing a step S6.9, and otherwise, executing a step S6.7.
S6.7: and arranging the transfer centers according to the comprehensive priority.
S6.8: and (6) loading the vehicles in descending order according to the package cargo quantity, and going to the step S6.6.
S6.9: the assigned vehicle results are recorded into a result set.
S6.10: and (4) judging whether all the vehicles are optimized, if so, executing the step S6.12, and otherwise, executing the step S6.11.
S6.11: the shortest path is planned for the nodes that the vehicle passes through and it goes to step S6.10.
S6.12: and reading the result set and outputting the optimal solution.
Correspondingly, as shown in fig. 6, the invention also discloses an express delivery vehicle transportation scheduling system, which includes:
and the composition unit 1 is used for acquiring the intra-area transfer center set and constructing a vehicle transportation network diagram.
And the set building unit 2 is used for building a port entry express item task set, a port exit express item task set and a transport vehicle set according to the yard clearing information of the transfer center of the express company.
And the model building unit 3 is used for building a vehicle optimization scheduling model of a sharing website and determining an optimization target and a constraint condition.
And the strategy configuration unit 4 is used for configuring the first-adapted express mail combination strategy based on descending order.
And an algorithm configuration unit 5 configured with a two-stage algorithm based on the comprehensive priority.
And the calculating unit 6 is used for scheduling the vehicles by adopting a two-stage algorithm based on comprehensive priority based on the descending order first-adapted express delivery combination strategy.
Correspondingly, the invention also discloses express vehicle transportation and dispatching equipment, which comprises:
a memory for storing a computer program;
a processor for implementing the express vehicle transportation scheduling method steps as described in any of the above when executing the computer program.
Those skilled in the art will readily appreciate that the techniques of the embodiments of the present invention may be implemented as software plus a required general purpose hardware platform. Based on such understanding, the technical solutions in the embodiments of the present invention may be embodied in the form of a software product, where the computer software product is stored in a storage medium, such as a usb disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and the like, and the storage medium can store program codes, and includes instructions for enabling a computer terminal (which may be a personal computer, a server, or a second terminal, a network terminal, and the like) to perform all or part of the steps of the method in the embodiments of the present invention. The same and similar parts in the various embodiments in this specification may be referred to each other. Especially, for the terminal embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant points can be referred to the description in the method embodiment.
In the embodiments provided by the present invention, it should be understood that the disclosed system, system and method can be implemented in other ways. For example, the above-described system embodiments are merely illustrative, and for example, the division of the units is only one logical functional division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, systems or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional modules in the embodiments of the present invention may be integrated into one processing unit, or each module may exist alone physically, or two or more modules are integrated into one unit.
Similarly, each processing unit in the embodiments of the present invention may be integrated into one functional module, or each processing unit may exist physically, or two or more processing units are integrated into one functional module.
The invention is further described with reference to the accompanying drawings and specific embodiments. It should be understood that these examples are for illustrative purposes only and are not intended to limit the scope of the present invention. Further, it should be understood that various changes or modifications of the present invention may be made by those skilled in the art after reading the teaching of the present invention, and these equivalents also fall within the scope of the present application.

Claims (3)

1. An express delivery vehicle transportation scheduling method is characterized by comprising the following steps:
s1: acquiring a regional transfer center set and constructing a vehicle transportation network diagram;
s2: establishing an entry and exit express task set and a transport vehicle set according to the clearing information of a transfer center of an express company;
s3: establishing a vehicle optimized dispatching model of a sharing network point, and determining an optimized target and a constraint condition;
s4: configuring an express item combination strategy based on descending order first-time adaptation;
s5: configuring a two-stage algorithm based on comprehensive priority;
s6: based on the descending order first-time adaptive express item combination strategy, a two-stage algorithm based on comprehensive priority is adopted for vehicle scheduling;
the step S1 includes:
a vehicle co-operating network is defined using (V, E), where V ═ V, {0,1,2 0 ∪V 1 Is a set of nodes, V 0 0 is a shared dot, V 1 N is a set of transit centers, and n is the number of transit centers; e { (i, j) | (i, j) ∈ V } is an edge set between nodes, each edge (i, j) ∈ E represents an optimal route from the node i to the node j, and d ij Representing the distance of the edge (i, j) which satisfies the symmetry, i.e., d ij ＝d ji The distance between the same nodes is 0, i.e. d ii ＝0，i∈V；
The step S2 includes the following steps:
s2.1: let P be { P ═ P 1 ,p 2 ,…,p n Is the set of all the taken quantities of each transit center in a certain period, p i Taking the quantity of the workpieces at a transfer center i; let D ═ D 1 ,d 2 ,…,d n D is the set of all delivered quantities of each transfer center in a certain period of time i The quantity of the delivered parts at the transfer center i; for each transit centre i, t i Is the latest pick-up time of the pick-up task i, c i (t i ) For a time penalty cost according to the rules of a hard time window, c i For a great time penalty cost, the pickup time of the vehicle must be t i Within time, if late, then receive a time penalty c i ＝c(t-t i )；
S2.2: let K be { K ═ K 1 ,k 2 ,…,k v Is the set of available vehicles, where v is the number of vehicles, l k Is the maximum load capacity, s, of the vehicle k k Representing the average running speed of the vehicle k, wherein the vehicle belongs to the sharing network point, starts from the sharing network point and finally returns to the sharing network point;
the step S3 includes:
use of
Figure FDA0003723604870000021
Indicating whether the vehicle k is traveling directly from point i to point j, where,
Figure FDA0003723604870000022
k is K, i is V, j is V, and if so, then
Figure FDA0003723604870000023
Otherwise
Figure FDA0003723604870000024
Using y i,k Indicating that the vehicle k is full of the pick-up of the transfer center i, where k is∈K，i∈V；
Using z i,k The method comprises the following steps of (1) representing that a vehicle K fully sends a part to a transfer center i, wherein K belongs to K, i belongs to V;
using u i,k Indicates whether the vehicle k reaches a point i, where u i,k E {0,1}, K e K, i e V, if vehicle K reaches point i, then u is a i,k 1, otherwise u i,k ＝0；
Establishing a sharing network point vehicle optimization scheduling model, which specifically comprises the following formula:
Figure FDA0003723604870000025
Figure FDA0003723604870000026
wherein the constraint condition comprises the following formula:
Figure FDA0003723604870000027
Figure FDA0003723604870000028
Figure FDA0003723604870000029
Figure FDA00037236048700000210
Figure FDA00037236048700000211
Figure FDA0003723604870000031
Figure FDA0003723604870000032
Figure FDA0003723604870000033
Figure FDA0003723604870000034
Figure FDA0003723604870000035
u i,k ∈{0,1}i∈V,k∈K (13)
in the vehicle optimized dispatching model of the sharing network point, a formula (1) is an optimized objective function of the model and represents that the total transportation path of all vehicles is minimized, and a formula (2) is an optimized objective function of the model and represents that the transportation time cost of all vehicles is minimized; the formula (3) and the formula (4) represent the load constraint of the vehicle, and represent that the total weight of all express items of each pick-up and delivery can not exceed the maximum load of a delivery vehicle; formulas (5) and (6) show that the task of taking and sending the workpieces of each transfer center can be met; formulas (7) and (8) represent the distribution path constraint of the transfer center, and the vehicle only passes through the center of the picked and delivered goods once in each vehicle transportation task; the formula (9) and the formula (10) show that the quantity of the workpieces taken and delivered by any vehicle to the transfer center cannot exceed the total task quantity of the center; equation (11) represents vehicle end point constraints, with vehicles returning to the end shared dot 0 after each task group is complete; the formula (12) and the formula (13) are defined for decision variables;
the express item combination strategy based on descending order first adaptation comprises the following specific steps:
s4.1: inputting express mail set t ═ t 1 ,t 2 ,...,t n }；
S4.2: express item t for set t i The cargo quantities are arranged in descending order;
s4.3: judging whether all the express items are reasonably combined, if all the express items are combined, turning to the step S4.7, otherwise, turning to the step S4.4;
s4.4: setting the package count m to be 0, the package size to be the current combination grade, and the current package to be B 1 ,B 2 ,...,B m ；
S4.5: in B 1 ,B 2 ,...,B m Searching for the current express item t i Loading the first package, and if the first package cannot be loaded, opening a new package;
s4.6: judging whether all the parcels meet the grade requirement of 90 percent of standard amount, if so, turning to the step S4.7, otherwise, releasing the parcel B j The express item in the package is in the set t, the rest packages are stored, and the step S4.2 is carried out;
s4.7: storing the combined parcel set B, and finishing the express item combination strategy based on descending order first-time adaptation;
the step S5 specifically includes the following steps:
s5.1: input parcel set B ═ B 1 ,b 2 ,...,b n }；
S5.2: selecting the packages with the grade of one in the packages B, and distributing vehicles by the transfer centers to which the packages of the grade one belong;
s5.3: judging whether the vehicle only loads a single primary package, releasing the vehicle, recording the condition of completely loading the vehicle to a result set, and deleting the loaded primary package in the step B;
s5.4: starting from the current node v, calculating the priority of other nodes by integrating the time window and the distance, and arranging the priority in a descending order;
s5.5: selecting a node v ' with the highest priority, loading the rest packages in the node v ' in a descending order according to the weight, if the volume of the packages exceeds the capacity of the vehicles, recording the packages to a result set, distributing new vehicles, keeping the vehicles k to the next node if the remaining space still exists, and updating the v as v ';
s5.6: judging whether all central nodes are loaded, if so, executing a step S5.7, otherwise, executing a step S5.4;
s5.7: selecting non-primary parcel vehicle records in a result set, and performing shortest path planning on nodes passed by the vehicles;
s5.8: judging whether all multi-node vehicle paths in the result set are optimized, if so, executing a step S5.9, otherwise, executing a step S5.7;
s5.9: after the algorithm is finished, outputting a scheduling result;
the step S6 specifically includes the following steps:
s6.1: initializing an express item set t, a vehicle set K and a node set V;
s6.2: arranging all the express items in the express item set t in a descending order according to the express item weight;
s6.3: applying a descending order first-adapted express item combination strategy to package express items, and obtaining a package set B;
s6.4: loading the primary packages of each transfer center in the package set B independently;
s6.5: obtaining a residual package set B';
s6.6: judging whether all the transfer centers are loaded, if so, executing a step S6.9, otherwise, executing a step S6.7;
s6.7: arranging the transfer centers according to the comprehensive priority;
s6.8: loading the packages in descending order according to the package cargo quantity, and going to the step S6.6;
s6.9: recording the distributed vehicle results to a result set;
s6.10: judging whether all vehicles are optimized, if so, executing a step S6.12, otherwise, executing a step S6.11;
s6.11: planning the shortest path of the nodes passed by the vehicle, and turning to the step S6.10;
s6.12: and reading the result set and outputting the optimal solution.
2. An express delivery vehicle transportation scheduling system, comprising:
the composition unit is used for acquiring a regional transfer center set and constructing a vehicle transportation network diagram;
the system comprises a set building unit, a transport vehicle set and a control unit, wherein the set building unit is used for building an entry port express item task set, an exit port express item task set and a transport vehicle set according to express company transfer center clearing information;
the model building unit is used for building a vehicle optimization scheduling model of a sharing network point and determining an optimization target and a constraint condition;
the strategy configuration unit is used for configuring an express item combination strategy which is firstly adapted based on descending order;
the algorithm configuration unit is used for configuring a two-stage algorithm based on the comprehensive priority;
the calculating unit is used for scheduling the vehicles by adopting a two-stage algorithm based on comprehensive priority based on the descending order first-adapted express mail combination strategy;
the express delivery vehicle-based transportation scheduling system comprises the following steps: step S1 includes:
a vehicle co-operating network is defined using (V, E), where V ═ V, {0,1,2 0 ∪V 1 Is a set of nodes, V 0 0 is a shared dot, V 1 N is a set of transit centers, and n is the number of transit centers; e { (i, j) | (i, j) ∈ V } is an edge set between nodes, each edge (i, j) ∈ E represents an optimal route from the node i to the node j, and d ij Representing the distance of the edge (i, j) which satisfies the symmetry, i.e., d ij ＝d ji The distance between the same nodes is 0, i.e. d ii ＝0，i∈V；
Step S2 includes the following steps:
s2.1: let P be { P ═ P 1 ,p 2 ,…,p n Is the set of all the taken quantities of each transit center in a certain period, p i Taking the quantity of the workpieces at a transfer center i; let D ═ D 1 ,d 2 ,…,d n D is the set of all delivered quantities of each transfer center in a certain period of time i The quantity of the delivered parts at the transfer center i; for each transit centre i, t i Is the latest pick-up time of the pick-up task i, c i (t i ) For a time penalty cost according to the rules of a hard time window, c i Is aThe great time penalty cost is caused, and the pickup time of the vehicle must be t i Within time, if late, then receive a time penalty c i ＝c(t-t i )；
S2.2: let K be { K ═ K 1 ,k 2 ,…,k v Is the set of available vehicles, where v is the number of vehicles, l k Is the maximum load capacity, s, of the vehicle k k Representing the average running speed of the vehicle k, wherein the vehicle belongs to the sharing network point, starts from the sharing network point and finally returns to the sharing network point;
step S3 includes:
use of
Figure FDA0003723604870000071
Indicating whether the vehicle k is traveling directly from point i to point j, where,
Figure FDA0003723604870000072
k is K, i is V, j is V, and if so, then
Figure FDA0003723604870000073
Otherwise
Figure FDA0003723604870000074
Using y i,k The method comprises the following steps of (1) representing that a vehicle K fully takes a part from a transfer center i, wherein K belongs to K, i belongs to V;
using z i,k The method comprises the following steps of (1) representing that a vehicle K fully sends a part to a transfer center i, wherein K belongs to K, i belongs to V;
using u i,k Indicates whether the vehicle k reaches a point i, where u i,k E {0,1}, K e K, i e V, if vehicle K reaches point i, then u is a i,k 1, otherwise u i,k ＝0；
The vehicle optimal scheduling model of the sharing network point specifically comprises the following formula:
Figure FDA0003723604870000075
Figure FDA0003723604870000076
formula (1) is an optimized objective function thereof, and represents that the total transportation path of all vehicles is minimized;
formula (2) is a second optimization objective function thereof, which represents minimizing the transport time cost of all vehicles;
the constraints include the following formula:
Figure FDA0003723604870000077
Figure FDA0003723604870000078
Figure FDA0003723604870000079
Figure FDA0003723604870000081
Figure FDA0003723604870000082
Figure FDA0003723604870000083
Figure FDA0003723604870000084
Figure FDA0003723604870000085
Figure FDA0003723604870000086
Figure FDA0003723604870000087
u i,k ∈{0,1}i∈V,k∈K (13)
the express item combination strategy based on descending order first adaptation comprises the following specific steps:
s4.1: inputting an express item set;
s4.2: arranging the sets t in descending order of the cargo quantity of the express;
s4.3: judging whether all the express items are reasonably combined, if all the express items are combined, turning to the step S4.7, and if not, turning to the step S4.4;
s4.4: setting a parcel count m to be 0, wherein the parcel size is the current combination grade, and the current parcel size is;
s4.5: searching and loading a first package which can be loaded with the current express, and opening a new package if the first package cannot be loaded;
s4.6: judging whether all the parcels meet the grade requirement of 90% of the standard quantity, if so, turning to the step S4.7, otherwise, releasing the express mails in the parcels to the set t, saving the rest parcels, and turning to the step S4.2;
s4.7: storing the combined parcel set B, and finishing the express item combination strategy based on descending order first-time adaptation;
the flow of the two-stage algorithm based on the comprehensive priority specifically comprises the following steps:
s5.1: inputting a package set;
s5.2: selecting the packages with the grade of one in the packages B, and distributing vehicles by the transfer centers to which the packages of the grade one belong;
s5.3: judging whether the vehicle only loads a single primary package, releasing the vehicle, recording the condition of completely loading the vehicle to result, and deleting the loaded primary package in the step B;
s5.4: starting from the current node v, calculating the priority of other nodes by integrating the time window and the distance, and arranging the priority in a descending order;
s5.5: selecting a node v ' with the highest priority, loading the rest packages in the node v ' in a descending order according to the weight, if the volume of the packages exceeds the capacity of the vehicles, recording the packages to a result, distributing a new vehicle, keeping the vehicle k to the next node if the remaining space still exists, and updating the v as v ';
s5.6: judging whether all central nodes are loaded, if so, executing a step S5.7, otherwise, executing a step S5.4;
s5.7: selecting non-primary package vehicle records in the result, and performing shortest path planning on nodes passing through in the vehicle;
s5.8: judging whether all multi-node vehicle paths of result are optimized, if so, executing a step S5.9, otherwise, executing a step S5.7;
s5.9: after the algorithm is finished, outputting a scheduling result;
step S6 is based on the first express item combination strategy of descending order, adopts two-stage algorithm based on comprehensive priority to carry out vehicle dispatching, and concretely comprises the following steps:
s6.1: initializing an express item set t, a vehicle set K and a node set V;
s6.2: arranging all the express items in the express item set t in a descending order according to the express item weight;
s6.3: applying a descending order first-adapted express item combination strategy to package express items, and obtaining a package set B;
s6.4: loading the primary packages of each transfer center in the package set B independently;
s6.5: obtaining a residual package set B';
s6.6: judging whether all the transfer centers are loaded, if so, executing a step S6.9, otherwise, executing a step S6.7;
s6.7: arranging the transfer centers according to the comprehensive priority;
s6.8: loading the packages in descending order according to the package cargo quantity, and going to the step S6.6;
s6.9: recording the distributed vehicle results to a result set;
s6.10: judging whether all vehicles are optimized, if so, executing a step S6.12, otherwise, executing a step S6.11;
s6.11: planning the shortest path of the nodes passed by the vehicle, and turning to the step S6.10;
s6.12: and reading the result set and outputting the optimal solution.
3. An express delivery vehicle transportation scheduling apparatus, comprising:
a memory for storing a computer program;
a processor for implementing the express vehicle transport scheduling method steps of claim 1 when executing the computer program.
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