Effect of switching in hybridized optimization techniques: A case study in production systems

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.