Grasp - Evolution For Constraint Satisfaction Problems
GECCO06: Genetic and Evolutionary Computation Conference Seattle Washington USA July, 2006(2006)
摘要
There are several evolutionary approaches for solving random binary Constraint Satisfaction Problems (CSPs). In most of these strategies we find a complex use of information regarding the problem at hand. Here we present a hybrid Evolutionary Algorithm that outperforms previous approaches in terms of effectiveness and compares well in terms of efficiency. Our algorithm is conceptual and simple, featuring a GRASP-like (GRASP stands for Greedy Randomized Adaptive Search Procedure) mechanism for genotype-to-phenotype mapping, and without considering any specific knowledge of the problem. Therefore, we provide a simple algorithm that harnesses generality while boosting performance.
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关键词
evolutionary combinatorial optimization,random binary CSPs,constraint handling,heuristics,hybridization
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