Abstract
The Travelling Salesman Problem (TSP) is one of the most widely studied optimization problems due to its many applications in domains such as logistics, planning, routing and scheduling. Approximation algorithms to address this NP-hard problem include genetic algorithms, ant colony systems and simulated annealing. This paper concentrates on the evolutionary approaches to TSP based on permutation encoded individuals. A comparative analysis of several recombination operators is presented based on computational experiments on a set of TSP instances. Numerical results emphasize a good performance of two proposed crossover schemes: best-worst recombination and best order recombination which take into account information from the global best and/or worst individuals besides the genetic material from parents.
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Gog, A., Chira, C. (2011). Comparative Analysis of Recombination Operators in Genetic Algorithms for the Travelling Salesman Problem. In: Corchado, E., Kurzyński, M., Woźniak, M. (eds) Hybrid Artificial Intelligent Systems. HAIS 2011. Lecture Notes in Computer Science(), vol 6679. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21222-2_2
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DOI: https://doi.org/10.1007/978-3-642-21222-2_2
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