Abstract
Recently, many kinds of approximate optimization methods have been proposed. The ant system (AS), which is originally proposed by Dorigo et al, is one such algorithm. To improve the basic performance of the AS algorithm, we developed the AS into a multiple ant colonies system (MACS) by introducing multiple colonies and colony-level interactions. MACS showed better performance compared with ACO [Kawamura (2000)]. In this study, we implemented no special heuristic technique as is often used in approximate optimization methods; therefore, it is necessary to investigate the performance of MACS with some heuristics for further development of MACS. In this paper, we implement 2-opt heuristic to the MACS for more powerful performance for solving TSPs.
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Kawamura, H., Yamamoto, M., Ohuchi, A. (2002). Improved Multiple Ant Colonies System for Traveling Salesman Problems. In: Kozan, E., Ohuchi, A. (eds) Operations Research/Management Science at Work. International Series in Operations Research & Management Science, vol 43. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-0819-9_3
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DOI: https://doi.org/10.1007/978-1-4615-0819-9_3
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