Uniform Experimental Design of Constrained Region Based on Evolutionary Algorithm

doi:10.16182/j.issn1004731x.joss.20-0189

Abstract

Abstract: The parameters of a simulation system are usually generated by the experimental design. Aiming at high design difficulty and computational cost of the uniform experimental design, of the constraint region, a two-stage differential evolutionary algorithm is further improved. The design is modeled as a constrained optimization problem. A strategy combining distribution estimation algorithm (EDA) and differential evolution (DE) is adopted. A point-deletion method is proposed to reduce the time complexity of optimizing the population uniformity. To demonstrate the advantages, the test instances and engineering applications are used in experimental analysis. The experimental results show that the performance, stability, and computational complexity of the proposed algorithm are better than those of the original algorithm.

Key words: uniform experimental design, constrained region, evolutionary algorithm, estimation of distribution algorithm, differential evolution

CLC Number:

Wei Jianing, Hao Hao, Chang Qutong, Lin Tao, Zhang Hu. Uniform Experimental Design of Constrained Region Based on Evolutionary Algorithm[J]. Journal of System Simulation, 2021, 33(7): 1591-1599.

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