Title :
A Max-Min Ant System with two colonies and its application to Traveling Salesman Problem
Author :
Xiaofan Zhou ; Liqing Zhao ; Zewei Xia ; Ronglong Wang
Author_Institution :
Grad. Sch. of Eng., Univ. of Fukui, Fukui, Japan
Abstract :
Based on the good performance of Max-Min Ant System (MMAS) in solving the Traveling Salesman Problem (TSP), a Max-Min Ant System with Two Colonies is proposed for the combinatorial optimization problems in this paper. This method is motivated by the fact that there are many colonies of ants in the natural world. In the proposed method, ants search solutions by cooperating with each other in the same colony until no better solution is found after a certain time period. Then, new pheromone distributions are built by communication between the two colonies. Basing on the new pheromone distribution, ants start their search procedure again in each separate colony. The proposed method is tested by simulating some TSP instances and simulation results show that the proposed algorithm performs better than the traditional ACO algorithms.
Keywords :
minimax techniques; search problems; travelling salesman problems; MMAS; TSP; combinatorial optimization problems; max-min ant system; pheromone distributions; search procedure; traveling salesman problem; two colonies; Ant colony optimization; Approximation algorithms; Cities and towns; Optimization; Simulation; Traveling salesman problems; Vehicles;
Conference_Titel :
Advanced Computational Intelligence (ICACI), 2012 IEEE Fifth International Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4673-1743-6
DOI :
10.1109/ICACI.2012.6463177