A hybrid genetic algorithm for job shop scheduling

A hybrid genetic algorithm for job shop scheduling

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Article ID: iaor20021183
Country: South Korea
Volume: 26
Issue: 2
Start Page Number: 59
End Page Number: 68
Publication Date: Jun 2001
Journal: Journal of the Korean ORMS Society
Authors: ,
Keywords: job shop, genetic algorithms
Abstract:

The job shop scheduling problem is not only NP-hard, but is one of the well known hardest combinatorial optimization problems. The goal of this research is to develop an efficient scheduling method based on hybrid genetic algorithm to address job shop scheduling problem. In this scheduling method, generating method of initial population, new genetic operator, selection method are developed. The scheduling method based on genetic algorithm are tested on standard benchmark job shop scheduling problem. The results are compared with another genetic algorithm-based scheduling method. Compared to traditional genetic algorithm, the proposed approach yields significant improvement at a solution.

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