A genetic algorithm (GA) is applied to an optimal scheduling problem for a large-scale complex manufacturing system. The system is operated in a job shop mode with additional constraints and during a long scheduling period. In order to obtain a good suboptimal solution, a GA is designed by introducing several ideas and heuristics for constructing the individual description and the genetic operators. In the paper a long-period scheduling problem for a metal mold assembly process is considered as a case study. The effectiveness of the proposed algorithm is examined by a numerical computation carried out on the basis of large-scale real operation data.
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