A genetic algorithm methodology for complex scheduling problems

A genetic algorithm methodology for complex scheduling problems

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Article ID: iaor19992935
Country: United States
Volume: 46
Issue: 2
Start Page Number: 199
End Page Number: 211
Publication Date: Mar 1999
Journal: Naval Research Logistics
Authors: ,
Keywords: combinatorial analysis
Abstract:

This paper considers the scheduling problem to minimize total tardiness given multiple machines, ready times, sequence dependent setups, machine downtime and scarce tools. We develop a genetic algorithm based on random keys representation, elitist reproduction, Bernoulli crossover and immigration type mutation. Convergence of the algorithm is proved. We present computational results on data sets from the auto industry. To demonstrate robustness of the approach, problems from the literature of different structure are solved by essentially the same algorithm.

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