A Multi-objective Version of the Lin-Kernighan Heuristic for the Traveling Salesman Problem release_lnkaaax5lra6vjiab3ehqeds5m

by Emerson Bezerra De Carvalho, Elizabeth Goldbarg, Marco Cesar Goldbarg

Published in Revista de Informática Teórica e Aplicada by Universidade Federal do Rio Grande do Sul.

2018   Volume 25, p48

Abstract

The Lin and Kernighan's algorithm for the single objective Traveling Salesman Problem (TSP) is one of the most efficient heuristics for the symmetric case. Although many algorithms for the TSP were extended to the multi-objective version of the problem (MTSP), the Lin and Kernighan's algorithm was still not fully explored. Works that applied the Lin and Kernighan's algorithm for the MTSP were driven to weighted sum versions of the problem. We investigate the LK from a Pareto dominance perspective. The multi-objective LK was implemented within two local search schemes and applied to 2 to 4-objective instances. The results  showed that the proposed algorithmic variants obtained better results than a state-of-the-art algorithm.
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