Chaotic ant swarm for the traveling salesman problem

• Published in: Nonlinear dynamics Vol. 65; no. 3; pp. 271 - 281
• Main Authors: Wei, Zhen, Ge, Fangzhen, Lu, Yang, Li, Lixiang, Yang, Yixian
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer Netherlands 01.08.2011; Springer Nature B.V
• Subjects: Algorithms; Automotive Engineering; Chaos theory; Classical Mechanics; Computer simulation; Control; Crossovers; Dynamical Systems; Engineering; Heuristic; Mapping; Mathematical models; Mechanical Engineering; Operators; Optimization; Original Paper; Swarm intelligence; Traveling salesman problem; Vibration; TSP; Combinational optimization; Swarm intelligence; Chaotic ant swarm; Global search
• ISSN: 0924-090X; 1573-269X
• DOI: 10.1007/s11071-010-9889-x

Chaotic ant swarm (CAS) is an optimization algorithm based on swarm intelligence theory, which has been applied to find the global optimum solution in continuous search space. However, it is not able to solve the combinational optimization problem directly, e.g., the traveling salesman problem (TSP). To tackle this problem, we propose a new method to solve the traveling salesman problem based on chaotic ant swarm, CAS-TSP for short. The CAS-TSP is developed by introducing a mapping from continuous space to discrete space, reverse operator and crossover operator into the CAS. Computer simulations demonstrate that the CAS-TSP is capable of generating optimal solution to instances of the TSPLIB in almost all test problems of sizes up to 150. Also a comparative computational study shows that this CAS-TSP algorithm is an efficient tool for solving TSP and this heuristic is competitive also with other heuristics.