TY - JOUR TI - A novel hybrid genetic algorithms and pattern search techniques for industrial production planning SN - 17939623 ID - scholars3149 A1 - Vasant, P. Y1 - 2012/// KW - Decision making; Genetic algorithms; Global optimization; Planning; Problem solving; Production control; Soft computing KW - Computational intelligent techniques; Degree of satisfaction; Global optimization method; Hybrid genetic algorithms; Industrial production; Pattern search; Production Planning; Traditional approaches KW - Optimization N1 - cited By 37 IS - 4 PB - World Scientific Publishing Co. Pte Ltd N2 - 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. VL - 3 JF - International Journal of Modeling, Simulation, and Scientific Computing UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84869751748&doi=10.1142%2fS1793962312500201&partnerID=40&md5=a7aafa9517923b080ed43581e4f8778b AV - none ER -