CN115730884A - Logistics transportation optimal path planning method - Google Patents
Logistics transportation optimal path planning method Download PDFInfo
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- CN115730884A CN115730884A CN202211376020.XA CN202211376020A CN115730884A CN 115730884 A CN115730884 A CN 115730884A CN 202211376020 A CN202211376020 A CN 202211376020A CN 115730884 A CN115730884 A CN 115730884A
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Abstract
The invention relates to the technical field of logistics, in particular to a logistics transportation optimal path planning method. Compared with the prior art, the method for planning the optimal path of the logistics transportation comprises the steps of firstly establishing a cargo transportation directed graph by taking a directed graph planning theory as a basis, and determining a physical conflict shunting point in a cargo transportation path; then converting the cargo transportation directed graph into a weighted directed graph; then, obtaining the optimal path plan of the logistics transportation by utilizing an improved ant colony algorithm; the method can select the road with the shortest route and the best road condition as the optimal path for logistics transportation in the specified time, so that the logistics transportation cost is reduced to the minimum, the requirements of customers on the aspect of transportation time can be met, and the benefits of logistics enterprises can be maximized.
Description
Technical Field
The invention relates to the technical field of logistics, in particular to a logistics transportation optimal path planning method.
Background
In recent years, the logistics transportation industry is used as a 'third benefit source', the driving effect on economic development is gradually highlighted, the position of the logistics industry in market economy is also obviously improved, and how to select the optimal logistics transportation path becomes an important problem faced by the logistics industry.
The optimal path planning method adopted by logistics enterprises at present has long logistics transportation time in practical application, and particularly has long transportation distance and more transportation points.
Therefore, a method needs to be designed, the optimal path of the logistics transportation is selected in the fastest time, and the method plays an important role in reducing the logistics transportation cost, saving the logistics transportation time and improving the logistics transportation service quality.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides a logistics transportation optimal path planning method.
The technical scheme adopted by the invention is as follows: the method for planning the optimal path of the logistics transportation comprises the following steps:
a. establishing a cargo transportation directed graph on the basis of a directed graph planning theory, and determining a physical conflict shunting point in a cargo transportation path;
b. converting the cargo transportation directed graph into a weighted directed graph;
c. and obtaining the logistics transportation optimal path plan by using the improved ant colony algorithm.
In order to better realize the invention, in the step a, the logistics transportation nodes are marked according to the distance from the intersection of the logistics transportation path to the starting point of the cargo transportation, a cargo transportation directed graph is established, and the intermediate nodes from the starting point to the end point of the logistics transportation are selected from the established cargo transportation directed graph to be used as core nodes and represented by a node G which represents the central position of the optimal path of the cargo transportation.
In order to better implement the method, in the step a, after the core nodes are determined, the logistics direction is set between the nodes, the unidirectional characteristic of the cargo transportation path is highlighted, and meanwhile, the real attribute of each road node is marked in the cargo transportation directed graph, wherein the real attribute comprises the coordinates of road intersections and the traffic direction.
In order to better implement the invention, in the step a, conflict points of the cargo transportation path are determined in the established cargo transportation directed graph, each conflict point is represented by a node H, and the conflict points are not considered as optimal path nodes when planning the optimal cargo transportation path.
In the step b, node attribute values of adjacent path nodes are standardized in the cargo transportation directed graph, cargo transportation route weights are determined, and adjacent node connecting routes are sequenced according to the weights, namely, the cargo transportation directed graph is converted into a weighted directed graph.
In order to better implement the present invention, in the step b, the weighted directed graph is represented by M, M = (X, [ Y ]), where X is a set of path nodes included in the cargo transportation path, and Y is a set of edges included in the cargo transportation path and connecting two path nodes.
In order to better implement the present invention, in said step c, the freight transportation starting point is set asq The end point of cargo transportation ispFrom freight vehiclesqTopIn the process of (1), the route is changed at any time according to the change of self condition and external condition, and if the number of the freight vehicles is n, each freight vehicle is driven by the following freight vehicleqTopIs expressed by the following formula:
wherein, the first and the second end of the pipe are connected with each other,Aindicating the freight vehicles fromqTopN represents the number of freight vehicles,S qi indicating the freight vehicles fromqTo the nodei The distance between the two or more of the two or more,S pi representing freight-vehicle slave nodesiTopThe distance between them.
To better implement the invention, transport time, transport cost and road smoothness are used as constraintsqTopSelecting a path with shortest transportation time, lowest cost and best road smoothness as an optimal path from the plurality of paths, wherein the transportation time constraint condition is represented by the following formula:
wherein the content of the first and second substances,T(j)a time factor representing the freight vehicle,t 1 indicating the freight vehicles fromqTopThe time required for the operation of the apparatus,t 2 indicating the freight vehicles fromqTopUpper limit of the maximum time allowed in the process of (1).
In order to better implement the invention, the constraint condition of the transportation cost is expressed by the following formula:
wherein the content of the first and second substances,C(j) representing a transportation cost factor consumed by the freight vehicle,g 1 represents the transportation cost required for the transportation of the freight vehicle;g 2 representing the maximum estimated transportation cost of the freight vehicle.
In order to better implement the present invention, the constraint condition of the road smoothness degree is expressed by the following formula:
wherein the content of the first and second substances,L(j) indicating the freight vehicles fromqTopA road smoothness factor of the path of;l 1 indicating freight vehicles fromqTopActual degree of smoothness of the path of (a);l 2 indicating the freight vehicles fromqTopThe worst degree of smoothness that can be allowed by the path of (c).
The invention has the beneficial effects that:
compared with the prior art, the method for planning the optimal path of the logistics transportation comprises the steps of firstly establishing a cargo transportation directed graph by taking a directed graph planning theory as a basis, and determining a physical conflict shunting point in a cargo transportation path; then converting the cargo transportation directed graph into a weighted directed graph; then, obtaining a logistics transportation optimal path plan by utilizing an improved ant colony algorithm; the method can select the road with the shortest route and the best road condition as the optimal path for logistics transportation in the specified time, so that the logistics transportation cost is reduced to the minimum, the requirements of customers on the aspect of transportation time can be met, and the benefits of logistics enterprises can be maximized.
Detailed Description
The following description provides many different embodiments, or examples, for implementing different features of the invention. The particular examples set forth below are intended as a brief description of the invention and are not intended as limiting the scope of the invention.
In this embodiment, the method for planning the optimal path of the logistics transportation includes the following steps:
a. establishing a cargo transportation directed graph on the basis of a directed graph planning theory, and determining a physical conflict shunting point in a cargo transportation path;
b. converting the cargo transportation digraph into a weighted digraph;
c. and obtaining the optimal path plan of the logistics transportation by utilizing the improved ant colony algorithm.
The method for planning the optimal path of the logistics transportation comprises the steps of firstly establishing a cargo transportation directed graph by taking a directed graph planning theory as a basis, and determining a physical conflict shunting point in a cargo transportation path; then converting the cargo transportation directed graph into a weighted directed graph; then, obtaining a logistics transportation optimal path plan by utilizing an improved ant colony algorithm; the method can select the road with the shortest route and the best road condition as the optimal path for logistics transportation in the specified time, so that the logistics transportation cost is reduced to the minimum, the requirements of customers on the aspect of transportation time can be met, and the benefits of logistics enterprises can be maximized.
Preferably, in the step a, a directed graph planning theory is used as a theoretical basis to determine a physical conflict diversion point in the cargo transportation path. And marking the logistics transportation nodes according to the distance from the logistics transportation path intersection to the goods transportation starting point, establishing a goods transportation directed graph, selecting intermediate nodes from the logistics transportation starting point to the goods transportation destination from the established directed graph as core nodes, and representing the central position of the goods transportation optimal path by using a node G. Then, a logistics direction is set between the nodes, so that the unidirectional characteristic of the cargo transportation path is highlighted. And simultaneously, marking the real attribute of each road node in the directed graph, wherein the real attribute comprises information such as the coordinates of the road intersection, the traffic direction and the like. And finally, corresponding relation is formed between the distance length of each starting node and the length of the distance between each starting node according to the length of the cargo transportation path in the directed graph. And determining conflict points of the cargo transportation path in the established directed graph of the cargo transportation, representing each conflict point by using a node H, and not considering the conflict points as optimal path nodes when planning the optimal path of the cargo transportation, so as to ensure that the point position in the planned optimal path of the cargo transportation is balanced and no path node conflict exists.
And marking the logistics transportation nodes according to the distance from the logistics transportation path intersection to the goods transportation starting point, establishing a goods transportation directed graph, selecting intermediate nodes from the logistics transportation starting point to the goods transportation destination from the established goods transportation directed graph as core nodes, and expressing the core nodes by using nodes G which represent the central position of the goods transportation optimal path.
Preferably, in the step b, in the cargo transportation directed graph, the node attribute values of the adjacent path nodes are standardized, the weight of the cargo transportation route is determined, and the connection routes of the adjacent nodes are sorted according to the weight, that is, the cargo transportation directed graph is converted into the weighted directed graph. The weighted directed graph is denoted by M, M = (X, [ Y ]]) Wherein, X is a set of path nodes included in the cargo transportation path, and Y is a set of edges included in the cargo transportation path and connecting two path nodes. Assume that a start node in a set of path nodes included in a cargo transportation path isqThe end node in the path node set included in the cargo transportation path ispThus, the problem of planning the optimal path for freight transportation can be described as the starting node in the weighted directed graph M of the freight transportation pathq To the destination nodepThe path with the smallest weight value does not contain the conflict point H.
Preferably, in the step c, the problem of the planning of the optimal path of the freight transportation is similar to the foraging behavior of the ant colony, so the planning of the optimal path of the logistics transportation adopts an ant colony algorithm, and the optimal path of the logistics transportation is planned through information transfer between the ant colonies. However, the situation that roads are not smooth often occurs in practical application of the path planned by the ant colony algorithm, so the optimal path for logistics transportation is planned by adopting the improved ant colony algorithm.
The cargo transportation starting point q is used as an ant colony to search for a food starting point, namely an ant nest, the cargo transportation end point p is used as an ant searched food place, and the ant colony changes a route at any time according to the change of self conditions and external conditions in the process of searching things. Set the starting point of cargo transportation asq The end point of the cargo transportation ispFrom freight vehiclesqTopIn the course of (2), the route is changed at any time according to the change of the self condition and the external condition, and if n freight vehicles are provided, each freight vehicle is driven by the same motorqTopIs represented by the following formula:
wherein the content of the first and second substances,Aindicating the freight vehicles fromqTopN represents the number of freight vehicles,S qi indicating freight vehicles fromqTo the nodei The distance between the two or more of the two or more,S pi representing freight-vehicle slave nodesiTopThe distance between them.
The transportation time, the transportation cost and the road smoothness degree are used as constraint conditions, so thatqTopThe path with the shortest transportation time, the lowest cost and the best smooth road is selected from the multiple paths as the optimal path, wherein the transportation time constraint condition is expressed by the following formula:
wherein, the first and the second end of the pipe are connected with each other,T(j)a time factor representing the freight vehicle,t 1 indicating freight vehicles fromqTopThe time required for the operation of the apparatus,t 2 indicating freight vehicles fromqTopUpper limit of the maximum time allowed in the process of (1). In which the freight vehicles are driven fromqTopRequired time of path required timet 1 Can not exceed the freight transport vehicleqToOf pMaximum upper time limit allowed in the processt 2 。
The constraint condition of the transportation cost is expressed by the following formula:
wherein the content of the first and second substances,C(j) representing a transportation cost factor consumed by the freight vehicle,g 1 represents the transportation cost required for the transportation of the freight vehicle;g 2 representing the maximum estimated transportation cost of the freight vehicle. In which the freight vehicles are driven fromqTopThe transport cost required to be consumed cannot exceed that of the freight vehicleqTopThe maximum transportation cost allowed in the process of (a).
The constraint condition of the road smoothness degree is expressed by the following formula:
wherein, the first and the second end of the pipe are connected with each other,L(j) indicating the freight vehicles fromqTopA road smoothness factor of the path of;l 1 indicating the freight vehicles fromqTopActual degree of smoothness of the path of (a);l 2 indicating freight vehicles fromqTopThe worst degree of smoothness that can be allowed by the path of (c). In which the freight vehicles are drivenqTopIs not able to pass over the freight carqTopThe worst degree of smoothness allowed in the process.
And then sequencing the paths according to the sequence from the largest weight to the smallest weight, and taking the path with the largest weight as the optimal path of the freight vehicle so as to finish the operation of the improved ant colony algorithm. The calculated path is identified in the cargo transportation directed graph and used as a cargo transportation optimal path, so that the modern logistics transportation optimal path planning based on the improved ant colony algorithm is completed, and a road with the shortest path and the best road condition can be selected as the logistics transportation optimal path in the specified time, so that the logistics transportation cost is reduced to the minimum, the requirements of customers on the transportation time can be met, and the benefit of logistics enterprises can be maximized.
The above description is intended to be illustrative of the preferred embodiment of the present invention and should not be taken as limiting the invention, but rather, the intention is to cover all modifications, equivalents, and alternatives falling within the spirit and scope of the invention.
Claims (10)
1. The method for planning the optimal path of the logistics transportation is characterized by comprising the following steps of:
establishing a cargo transportation directed graph by taking a directed graph planning theory as a basis, and determining a physical conflict shunting point in a cargo transportation path;
converting the cargo transportation digraph into a weighted digraph;
and obtaining the logistics transportation optimal path plan by using the improved ant colony algorithm.
2. The method for planning the optimal path for logistics transportation according to claim 1, wherein: in the step a, the logistics transportation nodes are marked according to the distance from the intersection of the logistics transportation path to the starting point of the freight transportation, a freight transportation directed graph is established, and the middle nodes from the starting point to the end point of the logistics transportation are selected from the established freight transportation directed graph to serve as core nodes and are represented by nodes G, wherein the node G represents the central position of the optimal path of the freight transportation.
3. The logistics transportation optimal path planning method according to claim 2, wherein: in the step a, after the core nodes are determined, the logistics direction is set between the nodes, the unidirectional characteristic of the cargo transportation path is highlighted, and meanwhile the real attribute of each road node is marked in the cargo transportation digraph, wherein the real attribute comprises the coordinates of a road intersection and the traffic direction.
4. The method for planning the optimal path for logistics transportation according to claim 3, wherein: in the step a, conflict points of the cargo transportation path are determined in the established cargo transportation directed graph, each conflict point is represented by a node H, and the conflict points are not considered as optimal path nodes when planning the optimal path of the cargo transportation.
5. The method for planning the optimal path for logistics transportation according to claim 4, wherein: in the step b, in the cargo transportation directed graph, node attribute values of adjacent path nodes are standardized, cargo transportation route weights are determined, and adjacent node connection routes are sequenced according to the weights, that is, the cargo transportation directed graph is converted into a weighted directed graph.
6. The logistics transportation optimal path planning method according to claim 5, wherein: in the step b, the weighted directed graph is represented by M, M = (X, [ Y ]), where X is a set of path nodes included in the cargo transportation path, and Y is a set of edges connecting two path nodes included in the cargo transportation path.
7. The method for planning the optimal path for logistics transportation according to claim 6, wherein: in the step c, the freight transportation starting point is set asq The end point of cargo transportation ispFrom freight vehiclesqTopIn the process of (1), the route is changed at any time according to the change of self condition and external condition, and the common freight vehicles are assumed to share
n, each freight vehicle is driven byqTopIs represented by the following formula:
wherein the content of the first and second substances,Aindicating freight vehicles fromqTopN represents the number of freight vehicles,S qi indicating the freight vehicles fromqTo nodei In between the distance between the first and second electrodes,S pi representing freight-vehicle slave nodesiTopThe distance between them.
8. The method for planning optimal path for logistics transportation according to claim 7, wherein the method is characterized in thatCharacterized in that: using the transportation time, the transportation cost and the road smoothness degree as constraint conditionsqTopSelecting a path with shortest transportation time, lowest cost and best road smoothness as an optimal path from the plurality of paths, wherein the transportation time constraint condition is represented by the following formula:
wherein the content of the first and second substances,T(j)a time factor representing the freight vehicle,t 1 indicating the freight vehicles fromqTopThe time required for the completion of the treatment,t 2 indicating the freight vehicles fromqTopUpper limit of the maximum time allowed in the process of (a).
9. The method for planning the optimal path for logistics transportation according to claim 8, wherein: the constraint condition of the transportation cost is expressed by the following formula:
wherein, the first and the second end of the pipe are connected with each other,C(j) representing a transportation cost factor consumed by the freight vehicle,g 1 represents the transportation cost required for the transportation of the freight vehicle;g 2 representing the maximum estimated transportation cost of the freight vehicle.
10. The method for planning the optimal path for logistics transportation according to claim 9, wherein: the constraint condition of the road smoothness degree is expressed by the following formula:
wherein the content of the first and second substances,L(j) indicating freight vehicles fromqTopA road smoothness factor of the path of;l 1 indicating freight vehicles fromqTopOf (2) aActual degree of smoothness of the road;l 2 indicating freight vehicles fromqTopThe worst degree of smoothness that can be allowed by the path of (c).
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| CN116562738A (en) * | 2023-07-10 | 2023-08-08 | 深圳市汉德网络科技有限公司 | Intelligent freight dispatching method, device, equipment and storage medium |
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| CN116562738A (en) * | 2023-07-10 | 2023-08-08 | 深圳市汉德网络科技有限公司 | Intelligent freight dispatching method, device, equipment and storage medium |
| CN116562738B (en) * | 2023-07-10 | 2024-01-12 | 深圳市汉德网络科技有限公司 | Intelligent freight dispatching method, device, equipment and storage medium |
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