Hybrid optimization techniques of pattern search and genetic algorithm: A case study in production system

Article type: Research Article

Authors: Vasant, Pandian

Affiliations: Department of Fundamental and Applied Sciences, Universiti Teknologi Petronas, Malaysia. E-mail: pvasant@gmail.com

Abstract: Intelligent computing has attracted many scientists, decision makers, and practicing researchers in recent years as powerful and novel intelligent techniques for solving unlimited number of complex real-world problems, particularly related to research area of optimization. Under the unpredictable and fuzzy environment, classical and traditional approaches are unable to obtain a complete solution with satisfaction for the practical optimization problems. Therefore, new global optimization methods are required to properly handle these issues. One of such methods is hybrid evolutionary computation, which is a generic, flexible, robust, and versatile method for solving the complex global optimization problems as well as implementing to practical applications.

Keywords: Pattern search, genetic algorithms, uncertainty, vagueness factor, production systems, switching approach

DOI: 10.3233/HIS-130175

Journal: International Journal of Hybrid Intelligent Systems, vol. 10, no. 4, pp. 179-190, 2013