A new and efficient ant-based heuristic method for solving the traveling salesman problem

: In this paper, we present an efficient metaheuristic approach for solving the problem of the traveling salesman. We introduce the multiple ant clans concept from parallel genetic algorithms to search solution space using different islands to avoid local minima in order to obtain a global minimum f...

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Bibliographic Details
Published in:Expert systems 2003-09, Vol.20 (4), p.179-186
Main Authors: Tsai, Cheng-Fa, Tsai, Chun-Wei, Tseng, Ching-Chang
Format: Article
Language:English
Subjects:
Algorithms
ant colony system
Artificial intelligence
Computer applications
Heuristic methods
metaheuristic approach
Road transport
Routing
traveling salesman problem
Travelling salesman problem
Vehicles
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Summary:: In this paper, we present an efficient metaheuristic approach for solving the problem of the traveling salesman. We introduce the multiple ant clans concept from parallel genetic algorithms to search solution space using different islands to avoid local minima in order to obtain a global minimum for solving the traveling salesman problem. Our simulation results indicate that the proposed novel traveling salesman problem method (called the ACOMAC algorithm) performs better than a promising approach named the ant colony system. This investigation is concerned with a real life logistics system design which optimizes the performance of a logistics system subject to a required service level in the vehicle routing problem. In this work, we also concentrate on developing a vehicle routing model by improving the ant colony system and using the multiple ant clans concept. The simulation results reveal that the proposed method is very effective and potentially useful in solving vehicle routing problems.
ISSN:0266-4720
1468-0394
DOI:10.1111/1468-0394.00242