Open AccessApplications of Intelligent Evolutionary Algorithms in Optimal Automation System Design
Author(s) -
Tung-Kuan Liu,
JyhHorng Chou
Publication year - 2011
Publication title -
international journal of automation and smart technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.148
H-Index - 10
ISSN - 2223-9766
DOI - 10.5875/ausmt.v1i1.100
Subject(s) - automation , scheduling (production processes) , computer science , evolutionary algorithm , field (mathematics) , systems engineering , electronic design automation , computer automated design , industrial engineering , systems design , manufacturing engineering , engineering , artificial intelligence , embedded system , operations management , mechanical engineering , mathematics , pure mathematics
[[abstract]]This paper proposes an intelligent evolutionary algorithm that can be applied in the design of optimal automation systems, and employs a multimodal six-bar mechanism optimization design, job shop production scheduling for the fishing equipment industry, and dynamic real-time production scheduling system design cases to show how the technique developed in this paper is highly effective at resolving optimal automation system design problems. Major breakthroughs in artificial intelligence continue to be made in the wake of advanced information technology developments, and the field of intelligent evolutionary algorithms has attracted a particularly large amount of attention from researchers and users in the artificial intelligence community. The successful optimization of automation system design requires interdisciplinary integration, and further requires the use of actual cases, verification, and improvement to ensure implementation in real-world applications