Hybrid Optimization for Decision Making in an uncertain Environment

In this book, the main significant contributions are formulation of a new non-linear membership function using fuzzy approach to capture and describe vagueness in the technological coefficients of constraints and intelligent solution methodology using hybrid meta-heuristics optimization techniques in an industrial production planning problems. The novel and innovative hybrid intelliegent such has genetic algorithms, simulated annealing, pattern search and fuzzy logic have been extensively used in this research work. Finally, it is concluded that hybrid optimization techniques are robust, less time-consuming, dependable, high quality solutions and an efficient productive tool for solving the non-linear real world problem in an uncertain industrial engineering environment. The hybrid line search with genetic algorithms and hybrid line search with simulated annealing techniques developed in this study are user friendly, easy-to-use and can serve as a teaching and research tool, besides being useful for practicing scientist, decision makers, managers and researchers in the area of industrial engineering, finance, economics and management science.