Improved QPSO with Selected Random Mean for Electromagnetic Problems

A. Duca
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Abstract

A new QPSO (Quantum-behaved Particle Swarm Optimization) with selected random mean is proposed in this paper for solving electromagnetic optimization problems. The selection procedure is a probabilistic mechanism indirectly based on the fitness measure of the solutions, solutions which are candidates for the QPSO mean term. The selection is controlled through a locality search parameter which is adapted during the optimization process to improve the overall performance of the algorithm. To test the performances two benchmark electromagnetic functions are considered, namely TEAM22 and Loney’s solenoid
基于选择随机均值的电磁问题改进QPSO
针对电磁优化问题,提出了一种具有选择随机均值的量子粒子群优化算法。选择过程是一种间接基于解的适应度度量的概率机制,这些解是QPSO平均项的候选解。通过在优化过程中调整局部搜索参数来控制选择,以提高算法的整体性能。为了测试性能,考虑了两个基准电磁功能,即TEAM22和Loney 's螺线管
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