%X 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.
%K 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
%L scholars3149
%J International Journal of Modeling, Simulation, and Scientific Computing
%O cited By 37
%N 4
%R 10.1142/S1793962312500201
%D 2012
%I World Scientific Publishing Co. Pte Ltd
%V 3
%A P. Vasant
%T A novel hybrid genetic algorithms and pattern search techniques for industrial production planning