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Multiple Criteria Lot-Sizing in a Foundry Using Evolutionary Algorithms

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Book cover Evolutionary Multi-Criterion Optimization (EMO 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3410))

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Abstract

The paper describes the application of multiobjective evolutionary algorithms in multicriteria optimization of operational production plans in a foundry, which produces iron castings and uses hand molding machines. A mathematical model that maximizes utilization of the bottleneck machines and minimizes backlogged production is presented. The model includes all the constraints resulting from the limited capacities of furnaces and machine lines, limited resources, customers requirements and the requirements of the manufacturing process itself. Test problems based on real production data were used for evaluation of the different evolutionary algorithm variants. Finally, the plans were calculated for a nine week rolling planning horizon and compared to real historical data.

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© 2005 Springer-Verlag Berlin Heidelberg

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Duda, J., Osyczka, A. (2005). Multiple Criteria Lot-Sizing in a Foundry Using Evolutionary Algorithms. In: Coello Coello, C.A., Hernández Aguirre, A., Zitzler, E. (eds) Evolutionary Multi-Criterion Optimization. EMO 2005. Lecture Notes in Computer Science, vol 3410. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-31880-4_45

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  • DOI: https://doi.org/10.1007/978-3-540-31880-4_45

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-24983-2

  • Online ISBN: 978-3-540-31880-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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