电磁场逆问题数值分析的多目标量子进化算法

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Abstract A vector quantum-inspired evolutionary algorithm(QEA), excluding the overly complex genetic operations of conventional evolutionary algorithms, is proposed for solving multi-objective inverse problems. A fitness assignment formula considering both the number of improvements in the whole objective functions and the amount of the improvement in a specified objective function is proposed. Also, the information sharing and the increment angle updating components of the scalar QEA are redesigned in accordance with the features of multi-objective inverse problems. Numerical results on a case study are presented to show the feasibility and merit of the proposed vector QEA.

Key words： Evolutionary algorithm inverse problem multi-objective optimization quantum computing electromagnetic fields

Received: 05 June 2013 Published: 05 November 2014

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TM153

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	Wang Ning
	Yang Shiyou

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Wang Ning,Yang Shiyou. A Vector Quantum-Inspired Evolutionary Algorithm Applied to Multi-Objective Inverse Problems[J]. Transactions of China Electrotechnical Society, 2014, 29(5): 49-53.

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http://dgjsxb.ces-transaction.com/EN/ OR http://dgjsxb.ces-transaction.com/EN/Y2014/V29/I5/49

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