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
Full text not available from this repository.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 |
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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 |