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
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.
In application/xml+jats
format
Archived Files and Locations
application/pdf 902.5 kB
file_si3pgofp2vfsri4byxi3oqpqa4
|
seer.ufrgs.br (web) web.archive.org (webarchive) |
article-journal
Stage
published
Date 2018-02-18
access all versions, variants, and formats of this works (eg, pre-prints)
Crossref Metadata (via API)
Worldcat
SHERPA/RoMEO (journal policies)
wikidata.org
CORE.ac.uk
Semantic Scholar
Google Scholar