Comparison of Differential Evolution Algorithms on the Mapping Between Problems and Penalty Parameters

Si, Chengyong; Shen, Jianqiang; Zou, Xuan; Wang, Lei

doi:10.1007/978-3-319-61824-1_46

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D) Investigation On Two Phases On the Same Cht1

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2020

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“…We should also point out that the parameter pf in SR is really important. If pf is set as 0.5, no feasible solutions will be found in all the functions except g08 and g12, the two functions whose best objective function value can be found with any penalty parameter in penalty function method [24].…”

Section: D) Investigation On Two Phases On the Same Chtmentioning

confidence: 99%

On the Cooperation Between Evolutionary Algorithms and Constraint Handling Techniques: A Further Empirical Study

2020

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Cooperation between Evolutionary Algorithms (EAs) and Constraint Handling Techniques (CHTs) plays an important role in Constrained Optimization Evolutionary Algorithms (COEAs). A constrained composite differential evolution (C 2 oDE) sets a good example on the cooperation. This paper tries to further study the inner mechanism, i.e., the effect of different methods on generating and selecting solutions. In the solution generating part, a new method, which adopts stochastic ranking in selecting the best individual in the DE mutation operators, is proposed. In the solution selecting part, a new constraint handling technique combination is added. The experiments on benchmark functions from IEEE CEC2006 verify the effect. During the experiment, it is found that a new cooperation manner performs better than C 2 oDE, which reflects the importance of cooperation. INDEX TERMS constrained optimization, constraint handling techniques, differential evolution, cooperation manner.

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Section: D) Investigation On Two Phases On the Same Chtmentioning

confidence: 99%