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  -