Ant colony optimization-differential evolution fusion method for solving traveling salesman problems

A technique of traveling salesman problem and differential evolution, applied in the fusion field of ant colony optimization-differential evolution

Inactive Publication Date: 2009-09-02
BEIHANG UNIV
View PDF0 Cites 21 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

This method is an effective way to solve large-scale complex optimization problems such as the traveling salesman problem, and at the same time, the present invention can also be applied to other complex intelligent optimization problems

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Ant colony optimization-differential evolution fusion method for solving traveling salesman problems
  • Ant colony optimization-differential evolution fusion method for solving traveling salesman problems
  • Ant colony optimization-differential evolution fusion method for solving traveling salesman problems

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0088] In order to verify the superiority of the improved ant colony optimization-differential evolution optimization algorithm when solving the traveling salesman problem, the present invention utilizes 48 cities traveling salesman problem (Att48TSP) to carry out experiments, and its specific implementation steps are as follows:

[0089] Step 1: Parameter initialization: set the current number of iterations Nc=1, and set the maximum number of loop iterations Nc max =100, parameter assignment: m=30, α=2, β=4, ρ=0.7, Q=10, F=2, CR=0.5, Team=5.

[0090] Step 2: Input the city coordinate set C in the 48-city traveling salesman problem to be solved, the total number of cities is n=48, and calculate the path length d between city j and city k jk , and η jk =1 / d jk Let the initialization pheromone τ on the path connecting city j and city k j，k =1, assign all ants to each ant team, the number of ants in each team is T_m(i)=m / Team=6; place the ants of each team randomly on each cit...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses an ant colony optimization-differential evolution fusion method for solving traveling salesman problems, which comprises the following steps: (1) algorithm parameters are initialized; (2) an ant colony is initialized; (3) a first iteration is carried out; (4) a mutation operation and an interlace operation are carried out to the pheromones of various squads from the second generation, so as to generate new pheromones; (5) the first squad is selected; (6) the ants of each squad establish the respective optimal path in accordance with the primitive pheromones; (7) the ants of each squad establish the respective optimal path in accordance with the new pheromones; (8) the two optimal paths are compared to pick out the pheromones with a better result of path optimization; (9) the pheromones of various ant squads are updated and passed down to the next generation; (10) the sixth step is carried out again until all squads finish the calculation; (11) the optimal path of the current generation and the length thereof are determined; (12) the fourth step is carried out again to carry out the calculation of the next generation until the termination condition is met; and (13) the whole optimal path and the length thereof are determined. The method has better astringency and stronger global optimization capability and is an effective way to solve the large-scale and complicated optimization problems such as traveling salesman problems, etc.

Description

(1) Technical field [0001] The invention discloses an ant colony optimization (Ant Colony Optimization, AGO)-differential evolution (Differential Evolution, DE) fusion method for solving a traveling salesman problem, belonging to the technical field of applied artificial intelligence. (2) Background technology [0002] The Traveling Salesman Problem (TSP) is a classic combinatorial optimization problem. The classic traveling salesman problem can be described as: a salesman is going to sell goods in several cities. The salesman starts from one city and needs to go through all After the city, return to the starting point. How should the travel route be chosen so that the total travel time is the shortest. From the perspective of graph theory, the essence of this problem is to find a Hamiltonian circuit with the smallest weight in a weighted completely undirected graph. Since the feasible solution to this problem is the full permutation of all vertices, a combinatorial explos...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Applications(China)
IPC IPC(8): G06N3/12G06Q10/00G06Q10/04
Inventor 张祥银段海滨金季强
Owner BEIHANG UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap