一种利用进化计算技术内部推理求解csp的新方案

2006 Eighth International Symposium on Symbolic and Numeric Algorithms for Scientific Computing Pub Date : 2006-09-26 DOI:10.1109/SYNASC.2006.7

M. Ionita, Mihaela Breaban, Cornelius Croitoru

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引用次数: 1

摘要

推理与搜索相结合，产生了求解约束满足问题的成功方案。在此基础上，提出了在进化计算技术中使用推理的一般方案。遗传算法和粒子群优化启发式算法利用了小桶消除算法提供的自适应推理水平。实验结果证明了该方法在求解Max-CSP优化任务中的有效性。分析了推理/搜索的权衡

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A New Scheme of Using Inference Inside Evolutionary Computation Techniques to Solve CSPs

Combining inference and search produces successful schemes for solving constraint satisfaction problems. Based on this idea a general scheme which uses inference inside evolutionary computation techniques is presented. A genetic algorithm and the particle swarm optimization heuristic make use of adaptable inference levels offered by the mini-bucket elimination algorithm. Experimental results prove the efficiency of our approach in solving the Max-CSP optimization task. The inference/search trade-off is analyzed

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2006 Eighth International Symposium on Symbolic and Numeric Algorithms for Scientific Computing

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