Improving Constraint-activated Differential Evolution with Escape Vectors

  • 徐 邦瀚

Student thesis: Master's Thesis


In system design the best system designed under a simple experimental environment may not be suitable for application in real world if dramatic changes caused by uncertainties contained in the real world are considered To deal with the problem caused by uncertainties designers should try their best to get the most robust solution The most robust solution can be obtained by constrained min-max optimization algorithms In this thesis the scheme of generating escape vectors has been proposed to solve the problem of premature convergence of differential evolution After applying the proposed scheme to the constrained min-max optimization algorithm the performance of the algorithm could be greatly improved To evaluate the performance of constrained min-max optimization algorithms more complex test problems have also been proposed in this thesis Experimental results show that the improved constrained min-max optimization algorithm is able to achieve a 100% success rate on all considered test problems under limited accuracy
Date of Award2015 Aug 4
Original languageEnglish
SupervisorShu-Mei Guo (Supervisor)

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