Memetic search for the quadratic assignment problem

作者：

Highlights：

• We present a memetic algorithm (called BMA) for the well-known QAP.

• BMA integrates BLS within the population-based evolutionary computing framework.

• BMA is able to attain the best-known results for 133 out of 135 QAP benchmark instances.

• We provide insights on search landscapes and crossover operators for QAP.

摘要

•We present a memetic algorithm (called BMA) for the well-known QAP.•BMA integrates BLS within the population-based evolutionary computing framework.•BMA is able to attain the best-known results for 133 out of 135 QAP benchmark instances.•We provide insights on search landscapes and crossover operators for QAP.

论文关键词：Memetic algorithm,Local search,Landscape analysis,Quadratic assignment,Combinatorial optimization

论文评审过程：Available online 23 August 2014.

论文官网地址：https://doi.org/10.1016/j.eswa.2014.08.011