期刊
IEEE TRANSACTIONS ON CYBERNETICS
卷 47, 期 7, 页码 1743-1756出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TCYB.2016.2556742
关键词
Ant colony optimization (ACO); dynamic traveling salesman problem (DTSP); local search; memetic algorithm
类别
资金
- Engineering and Physical Sciences Research Council of U.K. [EP/K001310/1]
- Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior, Brazil [BEX 2380/14-5]
- EPSRC [EP/K001310/1] Funding Source: UKRI
- Engineering and Physical Sciences Research Council [EP/K001310/1] Funding Source: researchfish
For a dynamic traveling salesman problem (DTSP), the weights (or traveling times) between two cities (or nodes) may be subject to changes. Ant colony optimization (ACO) algorithms have proved to be powerful methods to tackle such problems due to their adaptation capabilities. It has been shown that the integration of local search operators can significantly improve the performance of ACO. In this paper, a memetic ACO algorithm, where a local search operator (called unstring and string) is integrated into ACO, is proposed to address DTSPs. The best solution from ACO is passed to the local search operator, which removes and inserts cities in such a way that improves the solution quality. The proposed memetic ACO algorithm is designed to address both symmetric and asymmetric DTSPs. The experimental results show the efficiency of the proposed memetic algorithm for addressing DTSPs in comparison with other state-of-the-art algorithms.
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