A novel hybrid genetic algorithms and pattern search techniques for industrial production planning

Vasant, P. (2012) A novel hybrid genetic algorithms and pattern search techniques for industrial production planning. International Journal of Modeling, Simulation, and Scientific Computing, 3 (4). ISSN 17939623

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Abstract

Soft computing has attracted many research scientists, decision makers and practicing researchers in recent years as powerful computational intelligent techniques, for solving unlimited number of complex real-world problems particularly related to research area of optimization. Under the uncertain and turbulence environment, classical and traditional approaches are unable to obtain a complete solution with satisfaction for the real-world problems on optimization. Therefore, new global optimization methods are required to handle these issues seriously. One such method is hybrid Genetic algorithms and Pattern search, a generic, flexible, robust, and versatile framework for solving complex problems of global optimization and search in real-world applications. © 2012 World Scientific Publishing Company.

Item Type: Article
Additional Information: cited By 37
Uncontrolled Keywords: Decision making; Genetic algorithms; Global optimization; Planning; Problem solving; Production control; Soft computing, Computational intelligent techniques; Degree of satisfaction; Global optimization method; Hybrid genetic algorithms; Industrial production; Pattern search; Production Planning; Traditional approaches, Optimization
Depositing User: Mr Ahmad Suhairi UTP
Date Deposited: 09 Nov 2023 15:51
Last Modified: 09 Nov 2023 15:51
URI: https://khub.utp.edu.my/scholars/id/eprint/3149

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