Abstract
In this paper we present a method for creating scheduling heuristics for parallel proportional machine scheduling environment and arbitrary performance criteria. Genetic programming is used to synthesize the priority function which, coupled with an appropriate meta-algorithm for a given environment, forms the priority scheduling heuristic. We show that the procedures derived in this way can perform similarly or better than existing algorithms. Additionally, this approach may be particularly useful for those combinations of scheduling environment and criteria for which there are no adequate scheduling algorithms.
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Jakobović, D., Jelenković, L., Budin, L. (2007). Genetic Programming Heuristics for Multiple Machine Scheduling. In: Ebner, M., O’Neill, M., Ekárt, A., Vanneschi, L., Esparcia-Alcázar, A.I. (eds) Genetic Programming. EuroGP 2007. Lecture Notes in Computer Science, vol 4445. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71605-1_30
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DOI: https://doi.org/10.1007/978-3-540-71605-1_30
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