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Hybrid Optimization Techniques for Industrial Production Planning: A Review

Hybrid Optimization Techniques for Industrial Production Planning: A Review
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Author(s): P. Vasant (Petronas University of Technology, Malaysia)
Copyright: 2014
Pages: 28
Source title: Handbook of Research on Novel Soft Computing Intelligent Algorithms: Theory and Practical Applications
Source Author(s)/Editor(s): Pandian M. Vasant (Petronas University of Technology, Malaysia)
DOI: 10.4018/978-1-4666-4450-2.ch002

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Abstract

This chapter provides a review of new hybrid methods that deal with the continuous local and global optimization problems for constrained industrial production planning problems. In this chapter, details about all types of optimization methods and approaches for the local and global optimization are highlighted. Altogether there are eight famous methods in hybrid evolutionary optimization. In this research, the hybridization between evolutionary algorithms and other heuristic approaches such as simulated annealing, line search, pattern search, and mesh adaptive direct search are adopted. A particular evolutionary computation approach of genetic algorithm is used in this hybridization process. An intelligent performance analysis table is suggested in this chapter which is significantly important for decision makers and implementers in the industrial engineering of production planning. A brief summary on the conclusions of the main contributions and achievements in this chapter as well as future research directions are highlighted.

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