An Evolutionary Multiagent Framework for Multiobjective Optimization. (21st April 2020)

• Record Type: Journal Article
• Authors: Zhang, Zihui; Han, Qiaomei; Li, Yanqiang; Wang, Yong; Shi, Yanjun
• Other Names: Insfran Pelozo Emilio Academic Editor.
• Is Part Of: Mathematical problems in engineering. Volume 2020(2020)
• Publication Date: 2020-04-21
• Subjects: Engineering mathematics -- Periodicals; 510.2462
• DOI: 10.1155/2020/9147649
• Languages: English
• ISSNs: 1024-123X

Abstract

Abstract : This article proposes an evolutionary multiagent framework of the co-operative co-evolutionary multiobjective model (CCMO-EMAS), specifically for equipment layout optimization in engineering. In this framework, each agent is set in a multiobjective cooperative co-evolutionary mode along with the algorithms and corresponding settings. In each iteration, agents are executed in turn, and each agent optimizes a subpopulation from system decomposition. Additionally, the collaboration mechanism is addressed to build complete solutions and evaluate individuals in the co-operative co-evolutionary algorithm. Each subpopulation is optimized once, and the corresponding agent is evaluated based on the improvement of the system memory. Moreover, the agent team is also evolved through an elite genetic algorithm. Finally, the proposed CCMO-EMAS framework is verified in a multimodule satellite equipment layout problem.