COMPARISON OF SIMULATED ANNEALING AND GENETIC ALGORITHM APPROACHES ON INTEGRATED PROCESS ROUTING AND SCHEDULING PROBLEM

COMPARISON OF SIMULATED ANNEALING AND GENETIC ALGORITHM APPROACHES ON INTEGRATED PROCESS ROUTING AND SCHEDULING PROBLEM

Today flexible manufacturing systems are highly popular due to their capability of quick response to customer needs. Although the advantages of flexible manufacturing systems cannot be denied, these systems also bring new issues on production planning side. Especially assigning machines to production operations and scheduling these operations with respect to machine constraints turn out to be an NP-Hard problem. In this study, the integrated process routing and scheduling problem is explained, and the performance of two different meta-heuristic techniques, which are genetic algorithms and simulated annealing, are compared in terms of solution time and quality.

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