A Multistrategy-Based Multiobjective Differential Evolution for Optimal Control in Chemical Processes. (16th September 2018)

• Record Type: Journal Article
• Authors: Xu, Bin; Chen, Xu; Huang, Xiuhui; Tao, Lili
• Other Names: Yang Zhile Academic Editor.
• Is Part Of: Complexity. Volume 2018(2018)
• Publication Date: 2018-09-16
• Subjects: Chaotic behavior in systems -- Periodicals; Complexity (Philosophy) -- Periodicals; 003
• DOI: 10.1155/2018/2317860
• Languages: English
• ISSNs: 1076-2787

Abstract

Abstract : Optimal control problems with multiple conflicting objectives in chemical processes are quite challenging. To solve such problems, we put forward a multistrategy-based multiobjective differential evolution, in which (1) a hybrid selection strategy is incorporated from the motivation of no single strategy outperforming all other ones in every stage; (2) a multipopulation strategy is applied to represent the main population and current optimum, and a cyclic crowding estimation is developed to maintain these optimum; and (3) a multimutation strategy is constructed to improve both exploration and exploitation ability. The effectiveness and efficiency of the proposed algorithm are validated by comparisons with some representative multiobjective evolutionary algorithms over 12 test instances. Moreover, the proposed algorithm is applied to solve 3 multiobjective optimal control problems in chemical processes. The obtained results indicate the efficiency and effectiveness of the proposed algorithm for solving multiobjective optimal control problems.