Discrete and continuous time representations and mathematical models for large production scheduling problems: A case study from the pharmaceutical industry
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References listed on IDEAS
- Christodoulos Floudas & Xiaoxia Lin, 2005. "Mixed Integer Linear Programming in Process Scheduling: Modeling, Algorithms, and Applications," Annals of Operations Research, Springer, vol. 139(1), pages 131-162, October.
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- Voll, Philip & Jennings, Mark & Hennen, Maike & Shah, Nilay & Bardow, André, 2015. "The optimum is not enough: A near-optimal solution paradigm for energy systems synthesis," Energy, Elsevier, vol. 82(C), pages 446-456.
- Silvente, Javier & Aguirre, Adrián M. & Zamarripa, Miguel A. & Méndez, Carlos A. & Graells, Moisès & Espuña, Antonio, 2015. "Improved time representation model for the simultaneous energy supply and demand management in microgrids," Energy, Elsevier, vol. 87(C), pages 615-627.
- Baumann, Philipp & Trautmann, Norbert, 2014. "A hybrid method for large-scale short-term scheduling of make-and-pack production processes," European Journal of Operational Research, Elsevier, vol. 236(2), pages 718-735.
- Leachman, Robert C. & Johnston, Lenrick & Li, Shan & Shen, Zuo-Jun, 2014. "An automated planning engine for biopharmaceutical production," European Journal of Operational Research, Elsevier, vol. 238(1), pages 327-338.
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KeywordsProduction Scheduling Mixed integer linear programming Time representations;
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