Abstract
Optimizing flexible routing in flexible manufacturing systems ameliorates the efficiency of flexible manufacturing systems. In the present competitive market, accuracy in the planning stage plays an important role. Therefore, in this article, a production simulator system based on genetic algorithms is utilized to find the near-optimal flexible routing for flexible manufacturing systems. A combination of production simulator system and genetic algorithms is introduced to find the appropriate order of a set of operations for jobs that need to be operated on available machine tools in flexible manufacturing systems. In order to augment genetic algorithms, a matrix encoding method is incorporated. The proposed simulation is applied to numerical case studies of flexible routing for flexible manufacturing systems problem. The purpose of case studies is to demonstrate the successful applicability of the proposed method for flexible routing for flexible manufacturing systems problem.
References
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