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A Method for Optimizing Dynamic Traveling Salesman Problem Using Intelligent Swarm Algorithm Based on Reuse Strategy

A traveling salesman problem and technology of traveling salesman, applied in computing, data processing applications, forecasting, etc., can solve problems that are difficult to solve algorithms, NP-hard combination optimization, and unsolvable, etc., to reduce the search space and achieve considerable economic and social value , the effect of improving search efficiency

Active Publication Date: 2021-07-20
SOUTH CHINA UNIV OF TECH
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Problems solved by technology

Most of these problems are NP-hard combinatorial optimization problems, some traditional algorithms are difficult or impossible to solve, and the ant colony algorithm provides an effective means for solving these problems

Method used

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  • A Method for Optimizing Dynamic Traveling Salesman Problem Using Intelligent Swarm Algorithm Based on Reuse Strategy
  • A Method for Optimizing Dynamic Traveling Salesman Problem Using Intelligent Swarm Algorithm Based on Reuse Strategy
  • A Method for Optimizing Dynamic Traveling Salesman Problem Using Intelligent Swarm Algorithm Based on Reuse Strategy

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Embodiment

[0054] In this embodiment, the set-based particle swarm algorithm and ant colony algorithm are combined with the reuse strategy and applied to the optimization of the dynamic traveling salesman. The content of the invention can be mainly divided into the modeling of dynamic traveling salesman and the reuse strategy of historical search information.

[0055] 1) Modeling of dynamic traveling salesman:

[0056] exist figure 1 In the partial map shown, there are a total of 12 access nodes (a-l), assuming two situations:

[0057] i) When an unexpected event (traffic accident, road failure) occurs on the original shortest path (red dotted line) from h to a, the red solid line will become the current shortest path from h to a;

[0058] ii) In some cases, since point l does not need to be visited, the visit order of the original three nodes f, i, l changes from f→l→i to f→i, thus directly skipping node l. Based on these two real situations, this embodiment models them respectively ...

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Abstract

The invention discloses a method for optimizing a dynamic traveling salesman problem by using an intelligent group algorithm based on a reuse strategy. The traditional traveling salesman problem needs to find a Hamiltonian circuit with the least cost in a static search space. But in fact, some applications in the real world that can be modeled on the traveling salesman problem are not all static. The city sets and weight matrices in their problem models are dynamically changing. In a dynamic environment, the search results in the previous environment can be reused and learned by the group in the new environment. In this way, the search space of the problem can be narrowed, so that the algorithm can search for a better path in a shorter time. The present invention proposes a dynamic traveling salesman modeling method with more practical significance and a strategy for reusing historical search results. In the experiment, the dynamic performance of the method is tested by changing the setting environment to different degrees, and it is proved that This shows that the present invention is reasonable and effective under different dynamic environments.

Description

technical field [0001] The invention relates to the technical field of dynamic traveling salesman modeling and intelligent computing, in particular to a method for optimizing a dynamic traveling salesman problem by using an intelligent group algorithm based on a reuse strategy. Background technique [0002] The Traveling Salesman Problem (TSP) has been considered as a classic combinatorial optimization problem since it was proposed. The salesperson needs to find a route from a certain city node in a fixed undirected graph G={V,A,W} Start from the point and traverse all other city nodes once, and finally return to the shortest Hamiltonian circuit at the starting point, where V represents a set of given nodes (in different problem models, the representative objects of the nodes are different), and A represents the graph The set of all undirected edges in , W is the weight matrix about the undirected graph G. The value of each element in the matrix represents the distance from...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06Q10/04
CPCG06Q10/047
Inventor 张军陈伟能詹志辉
Owner SOUTH CHINA UNIV OF TECH
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