title: |
Stochastic Local Search Using the Search Space Smoothing Meta-Heuristic:A Case Study |
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publication: |
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part of series: |
Advances in Intelligent Systems Research | |
ISBN: |
978-90-78677-01-7 | |
ISSN: |
1951-6851 | |
DOI: |
doi:10.2991/jcis.2006.213 (how to use a DOI) | |
author(s): |
Sheqin Dong, Fan Guo, Jun Yuan, Rensheng Wang, Xianlong Hong |
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corresponding author: |
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publication date: |
October 2006 |
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keywords: |
Solution Space Smoothing, Stochastic Local Search, TSP |
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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. |
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copyright: |
©
Atlantis Press. This article is distributed under the
terms of the Creative Commons Attribution License, which permits
non-commercial use, distribution and reproduction in any medium,
provided the original work is properly cited. |
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full text: |