Abstract
In this paper we present a computational study of optimization methods for production scheduling problems which can be described by a job shop model. Contrary to most existing publications in this field our research focuses on the performance of these methods with respect to large-scale problem instances. The examined methods rely on a graph model as a solution representation and have originally been designed for problems of small size. We apply them to a set of semi-randomly generated problem instances whose properties have been transferred from common (smaller) benchmarks. The experiments are based on tardiness minimization and the results are evaluated in relation to a priority rule based heuristic.
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Braune, R., Wagner, S., Affenzeller, M. (2007). Optimization Methods for Large-Scale Production Scheduling Problems. In: Moreno Díaz, R., Pichler, F., Quesada Arencibia, A. (eds) Computer Aided Systems Theory – EUROCAST 2007. EUROCAST 2007. Lecture Notes in Computer Science, vol 4739. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75867-9_102
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DOI: https://doi.org/10.1007/978-3-540-75867-9_102
Publisher Name: Springer, Berlin, Heidelberg
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