A NOVEL HYBRID GENETIC ALGORITHMS AND PATTERN SEARCH TECHNIQUES FOR INDUSTRIAL PRODUCTION PLANNING

作     者：P.VASANT 

作者机构：Department of Fundamental and Applied Sciences University Technology PetronasMalaysia 

出 版 物：《International Journal of Modeling, Simulation, and Scientific Computing》 (建模、仿真和科学计算国际期刊（英文）)

年 卷 期：2012年第3卷第4期

页      面：132-150页

核心收录：

学科分类：08[工学] 0701[理学-数学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：Genetic algorithms Pattern search production planning optimal profit degree of satisfaction decision making. 

摘      要：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 *** the uncertain and turbulence environment,classical and traditional approaches are unable to obtain a complete solution with satisfaction for the real-world problems on ***,new global optimization methods are required to handle these issues *** 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.