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2011 Third International Conference on Knowledge and Systems Engineering
Improving Search Efficiency Adopting Hill-Climbing to Ant Colony Optimization for Constraint Satisfaction Problems
Hanoi, Vietnam
October 14-October 17
ISBN: 978-0-7695-4567-7
To efficiently solve large-scale constraint satisfaction problems, CSPs, we propose an ant colony optimization based meta-heuristics combined with the hill-climbing approach. In our method, in order to improve search inefficiency which happens due to slow reconstruction of assignments of values to variables in the naive ant system, AS, min-conflict hill-climbing is applied to some assignments constructed ones by AS. This method is applied to large-scale and hard binary CSP instances in phase transition regions, whose experimental simulations demonstrate that our method is more efficient than AS.
Citation:
Daiki Hayakawa, Kazunori Mizuno, Hitoshi Sasaki, Seiichi Nishihara, "Improving Search Efficiency Adopting Hill-Climbing to Ant Colony Optimization for Constraint Satisfaction Problems," kse, pp.200-204, 2011 Third International Conference on Knowledge and Systems Engineering, 2011
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