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Testing of Hybrid Genetic Algorithms for Structured Quadratic Assignment Problems

机译:结构二次分配问题的混合遗传算法测试

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摘要

In this paper, an efficient hybrid genetic algorithm (HGA) and its variants for the well-known combinatorial optimization problem, the quadratic assignment problem (QAP) are discussed. In particular, we tested our algorithms on a special type of QAPs, the structured quadratic assignment problems. The results from the computational experiments on this class of problems demonstrate that HGAs allow to achieve near-optimal and (pseudo-)optimal solutions at very reasonable computation times. The obtained results also confirm that the hybrid genetic algorithms are among the most suitable heuristic approaches for this type of QAPs.
机译:本文讨论了一种有效的混合遗传算法(HGA)及其变体,用于解决众所周知的组合优化问题,二次分配问题(QAP)。特别是,我们在一种特殊类型的QAP(结构化二次分配问题)上测试了我们的算法。关于此类问题的计算实验结果表明,HGA可以在非常合理的计算时间内实现接近最佳和(伪)最佳解。获得的结果还证实,混合遗传算法是此类QAP最合适的启发式方法。

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