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Erschienen in:
2012 | OriginalPaper | Buchkapitel
An Incremental Approach to Solving Dynamic Constraint Satisfaction Problems
verfasst von : Anurag Sharma, Dharmendra Sharma
Erschienen in: Neural Information Processing
Verlag: Springer Berlin Heidelberg
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Constraint satisfaction problems (CSPs) underpin many science and engineering applications. Recently introduced
intelligent constraint handling evolutionary algorithm
(ICHEA) in [14] has demonstrated strong potential in solving them through evolutionary algorithms (EAs). ICHEA outperforms many other evolutionary algorithms to solve CSPs with respect to success rate (SR) and efficiency. This paper is an enhancement of ICHEA to improve its efficiency and SR further by an enhancement of the algorithm to deal with local optima obstacles. The enhancement also includes a capability to handle dynamically introduced constraints without restarting the whole algorithm that uses the knowledge from already solved constraints using an incremental approach. Experiments on benchmark CSPs adapted as dynamic CSPs has shown very promising results.