Improved multi-objective constrained optimization differential evolution algorithm
Year: 2012
Type: article
Abstract: A novel multi-objective optimization differential evolution algorithm is proposed for solving constrained optimization problems.In the process of population evolution,the individuals generation based on good-point-set method is introduced into the evolutionary algorithm initial step.The constrained optimization problem is converted into a multi-objective optimization problem.The population is divided into Non-Pareto set and Pareto set based on multi-objective optimization technique.In order to improve global convergence of the proposed algorithm,DE/best/1 mutation scheme and DE/rand/1 mutation scheme are used to the Non-Pareto set and the Pareto set respectively.The experimental results show that the proposed algorithm can get high performance while dealing with various complex problems.
Author: Wen Long
Institution: Guizhou University of Finance and Economics
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W2347238817