Local optimization and the traveling salesman problem
Proceedings of the seventeenth international colloquium on Automata, languages and programming
LSMS'07 Proceedings of the Life system modeling and simulation 2007 international conference on Bio-Inspired computational intelligence and applications
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Correction heuristicsfor the traveling salesman problem (TSP), with the 2-Opt appliedas a postprocess, are studied with respect to their tour lengthsand computation times. This study analyzes the ’’2-Opt dependency,‘‘which indicates how the performance of the 2-Opt depends on theinitial tours built by the construction heuristics. In accordancewith the analysis, we devise a new construction heuristic, the recursive-selection with long-edge preference (RSL) method,which runs faster than the multiple-fragment method and producesa comparable tour when they are combined with the 2-Opt.