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Traveling salesman problem solving method based on improved ant colony algorithm

A technology of traveling salesman problem and ant colony algorithm, which is applied in the field of solving traveling salesman problem based on improved ant colony algorithm, can solve problems such as increasing algorithm complexity, local optimization of ant colony algorithm, etc. The effect of solving accuracy and increasing global search capability

Pending Publication Date: 2020-06-23
ZHEJIANG UNIVERSITY OF SCIENCE AND TECHNOLOGY
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Problems solved by technology

[0005] Introducing the ideas of other algorithms into the algorithm can speed up the convergence speed of the algorithm to a certain extent, but at the same time it also increases the complexity of the algorithm itself, and does not solve the problem that the ant colony algorithm is easy to fall into local optimum

Method used

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  • Traveling salesman problem solving method based on improved ant colony algorithm
  • Traveling salesman problem solving method based on improved ant colony algorithm
  • Traveling salesman problem solving method based on improved ant colony algorithm

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Embodiment Construction

[0020] refer to figure 1 , the present invention, the method comprises the following steps:

[0021] Step 1: Assignment of initial pheromone concentration: through the formula Complete the assignment of the initial pheromone concentration, in the formula, k 0 is a constant, d ij is the Euclidean distance between node i and node j, τ ij is the initial pheromone concentration of the path connecting node i and node j;

[0022] Step 2: assign ants to each node;

[0023] Step 3: Complete an iteration;

[0024] Step 4: Update each path pheromone;

[0025] Step 5: Judging "whether the optimal path has not changed within a period of time after the pheromone divergence point", if so, perform step 6; if not, perform step 7;

[0026] Step 6: Reset the pheromone matrix, and then perform Step 2;

[0027] Step 7: Judging "whether the algorithm has reached the maximum number of iterations", if yes, complete the solution; if not, perform step 2.

[0028] Specifically, the specific m...

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Abstract

The invention discloses a traveling salesman problem solving method based on an improved ant colony algorithm. The method comprises the following steps: step 1, assigning an initial pheromone concentration; 2, ants are distributed to all nodes; 3, completing one time of iteration; 4, updating each path pheromone; 5, judging whether the optimal path is still unchanged or not in a period of time after the pheromone divergence point, and if so, executing the step 6; if not, executing the step 7; 6, resetting the pheromone matrix, and executing the step 2; 7, judging whether the algorithm reachesthe maximum number of iterations or not, and if so, finishing solving; and if not, executing the step 2. By improving the ant colony algorithm, the ant colony algorithm can more effectively avoid thesituation that the algorithm is caught in local convergence in the process of solving the TSP problem, the global search ability of the algorithm is improved, and therefore the accuracy of result solving is improved.

Description

【Technical field】 [0001] The invention relates to the technical field of computers, in particular to the technical field of the traveling salesman problem solving method based on the improved ant colony algorithm. 【Background technique】 [0002] TSP problem (Traveling Salesman Problem) is also translated as traveling salesman problem and salesman problem. It is one of the famous problems in the field of mathematics. It describes the following scenario: a traveling businessman wants to visit various cities, the number of cities is n, the restriction is that each city can only be visited once and all cities must be visited, the optimization goal is to make it possible to visit all cities and finally return The total path length traveled by the traveling merchant to the starting point is the shortest. In the classic TSP problem, the path length between points is the straight-line distance between points. In this paper, the improved ant colony algorithm is applied to the solut...

Claims

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Application Information

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IPC IPC(8): G06Q10/04G06N3/00
CPCG06N3/006G06Q10/047
Inventor 徐书扬王海江潘华铮李海洋王黎航
Owner ZHEJIANG UNIVERSITY OF SCIENCE AND TECHNOLOGY
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