Stochastic Local Search Using the Search Space Smoothing Meta-Heuristic:A Case Study

DOI

10.2991/jcis.2006.213How to use a DOI?

Keywords

Solution Space Smoothing, Stochastic Local Search, TSP

Abstract

In this paper, two smoothing effects are firstly pointed out by analysis and by experiment on Traveling Salesman Problem(TSP) instances. We design a novel algorithm which runs stochastic local search under the SSS framework. The function determining the accepting probability of uphill moves is designed so that the algorithm can take advantage of the local smoothing effect ignored in original SSS. Experimental results on TSPLIB instances demonstrated that the performance of the new algorithm is much superior to traditional SSS approach.

Copyright

© 2006, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Sheqin Dong
AU  - Fan Guo
AU  - Jun Yuan
AU  - Rensheng Wang
AU  - Xianlong Hong
PY  - 2006/10
DA  - 2006/10
TI  - Stochastic Local Search Using the Search Space Smoothing Meta-Heuristic:A Case Study
BT  - Proceedings of the 9th Joint International Conference on Information Sciences (JCIS-06)
PB  - Atlantis Press
SP  - 437
EP  - 440
SN  - 1951-6851
UR  - https://doi.org/10.2991/jcis.2006.213
DO  - 10.2991/jcis.2006.213
ID  - Dong2006/10
ER  -