Proceedings of the 9th Joint International Conference on Information Sciences (JCIS-06)

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

Authors
Sheqin Dong 0, Fan Guo, Jun Yuan, Rensheng Wang, Xianlong Hong
Corresponding Author
Sheqin Dong
0Tsinghua University
Available Online October 2006.
DOI
https://doi.org/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.
Open Access
This is an open access article distributed under the CC BY-NC license.

Download article (PDF)

Proceedings
Part of series
Advances in Intelligent Systems Research
Publication Date
October 2006
ISBN
978-90-78677-01-7
ISSN
1951-6851
DOI
https://doi.org/10.2991/jcis.2006.213How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

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
PB  - Atlantis Press
SP  - 437
EP  - 440
SN  - 1951-6851
UR  - https://doi.org/10.2991/jcis.2006.213
DO  - https://doi.org/10.2991/jcis.2006.213
ID  - Dong2006/10
ER  -