A diversity-guided modified QPSO algorithm and its application in the optimization design of dry-type air-core reactors

作者：Zhang Chengfen^*; Zhao Yanzhen; Zou Jianlong; Ma Xikui

来源：Proceedings of the CSEE, 2012, 32(18): 108-115.

• Chaotic mutations
• Diversity
• Dry-type air-core reactors
• Optimization design
• Quantum-behaved particle swarm optimization

According to the premature convergence of the quantum-behaved particle swarm optimization (QPSO) algorithm in solving complex problems, a diversity-guided modified QPSO (DGMQPSO) algorithm is proposed. The algorithm extends the mixed-probability-distribution based QPSO algorithm by using the populations' diversity information to guide the search of the particles. The chaotic mutation is implemented to the position of the global optimal particle when the populations' diversity is less than the lower limit, so that the diversity of the populations is improved and the ability of jumping out of the local optimal solution is enhanced. Moreover, the optimization design results are analyzed by using the mutation of the different chaotic random sequence. The simulation results of a 50 kvar dry-type air-core reactor show that the DGMQPSO algorithm is of strong global search ability, good stability and excellent optimization performance.

• 出版日期2012