Article: Constrained evolution algorithm based on adaptive differential evolution Journal: International Journal of High Performance Computing and Networking (IJHPCN) 2018 Vol.11 No.3 pp.223 - 230 Abstract: Solving constrained optimisation is widely used in science and engineering, but the slow convergence speed and premature are the biggest problems researchers face. Research on a constrained evolution algorithm (CO-JADE) based on adaptive differential evolution (JADE) for solving the constrained optimisation problems is proposed in this paper. According to features of the Gaussian distribution, the Cauchy distribution and the mutation factor, we exploited the crossover probability of each individual to improve the search strategy. Aimed to effectively evaluate the relationship between the value of the objective function and the degree of constraint violation, the paper used an improved adaptive tradeoff model to evaluate the individuals of the population. This tradeoff model used different treatment scheme for different stages of the population and implemented on night standard test functions. The experimental shows that the CO-JADE has better accuracy and stability than the COEA/ODE and the HCOEA. Inderscience Publishers - linking academia, business and industry through research

Title: Constrained evolution algorithm based on adaptive differential evolution

Authors: Kangshun Li; Liang Zhong; Lei Zuo; Zhaopeng Wang

Addresses: College of Mathematics and Informatics, South China Agricultural University, Guangzhou, 510642, China; Shenzhen Suodi Statistician Company Limited, Shenzhen, 518000, China ' College of Mathematics and Informatics, South China Agricultural University, Guangzhou, 510642, China ' College of Mathematics and Informatics, South China Agricultural University, Guangzhou, 510642, China ' College of Mathematics and Informatics, South China Agricultural University, Guangzhou, 510642, China

Abstract: Solving constrained optimisation is widely used in science and engineering, but the slow convergence speed and premature are the biggest problems researchers face. Research on a constrained evolution algorithm (CO-JADE) based on adaptive differential evolution (JADE) for solving the constrained optimisation problems is proposed in this paper. According to features of the Gaussian distribution, the Cauchy distribution and the mutation factor, we exploited the crossover probability of each individual to improve the search strategy. Aimed to effectively evaluate the relationship between the value of the objective function and the degree of constraint violation, the paper used an improved adaptive tradeoff model to evaluate the individuals of the population. This tradeoff model used different treatment scheme for different stages of the population and implemented on night standard test functions. The experimental shows that the CO-JADE has better accuracy and stability than the COEA/ODE and the HCOEA.

Keywords: adaptive differential evolution; adaptive tradeoff model; constrained optimisation.

DOI: 10.1504/IJHPCN.2018.091893

International Journal of High Performance Computing and Networking, 2018 Vol.11 No.3, pp.223 - 230

Received: 16 Jan 2016
Accepted: 29 Apr 2016
Published online: 21 May 2018 *

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Title: Constrained evolution algorithm based on adaptive differential evolution

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