An Improvement of Differential Evolution for Nonlinear Optimization(<Special Issue>Information Systems and Human Sciences)

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概要

• 論文の詳細を見る

• This paper proposes a versatile heuristic solution algorithm for nonlinear programming problems. Differential Evolution (DE), proposed by Storn et al., has the following two issues: one is that the algorithm has a tendency to fall into a local optimal solution, and the other is that the algorithm cannot be applied to nonlinear programming problems with constraints directly. For searching widely in a feasible set, the movement of individuals and their evaluation function are improved. The efficiency of the solution algorithm is shown by applying it to various types and scales of non-linear programming problems.

• バイオメディカル・ファジィ・システム学会の論文

著者

• KATO Kosuke

  Faculty of Applied Information Science, Hiroshima Institute of Technology

• UNO Takeshi

  Institute of Socio-Arts and Sciences, The University of Tokushima

関連論文

• An Improvement of Differential Evolution for Nonlinear Optimization(Information Systems and Human Sciences)

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