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Iterated Local Search for Foundry Lot-sizing and Scheduling Problem with Setup Costs

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Języki publikacji
EN
Abstrakty
EN
The paper presents a novel Iterated Local Search (ILS) algorithm to solve multi-item multi-family capacitated lot-sizing problem with setup costs independent of the family sequence. The model has a direct application to real production planning in foundry industry, where the goal is to create the batches of manufactured castings and the sequence of the melted metal loads to prevent delays in delivery of goods to clients. We extended existing models by introducing minimal utilization of furnace capacity during preparing melted alloy. We developed simple and fast ILS algorithm with problem-specific operators that are responsible for the local search procedure. The computational experiments on ten instances of the problem showed that the presence of minimum furnace utilization constraint has great impact on economic and technological conditions of castings production. For all test instances the proposed heuristic is able to provide the results that are comparable to state-of-the art commercial solver.
Rocznik
Strony
161--164
Opis fizyczny
Bibliogr. 10 poz., rys., tab.
Twórcy
autor
  • AGH University of Science and Technology, Faculty of Management, ul. Gramatyka 10, 30-067 Kraków
autor
  • AGH University of Science and Technology, Faculty of Management, ul. Gramatyka 10, 30-067 Kraków
Bibliografia
  • [1] de Araujo, S.A., Arenales, M.N. & Clark, A.R. (2008). Lot sizing and furnace scheduling in small foundries. Computers & Operations Research. 35(3), 916-932. DOI: 10.1016/ j.cor.2006.05.010.
  • [2] Basiura, R., Duda, J. & Stawowy, A. (2015). Production scheduling for the one furnace – two casting lines system. Archives of Foundry Engineering. 15(spec.2), 3-6.
  • [3] Stawowy, A. & Duda, J. (2017). Coordinated production planning problem in a foundry. Archives of Foundry Engineering. 17(3), 133-138.
  • [4] Li, X., Guo, S., Liu, Y. & Du, B. (2017). A production planning model for make-to-order foundry flow shop with capacity constraint. Mathematical Problems in Engineering. 15 pages. DOI: 10.1155/2017/6315613.
  • [5] Karimi, B., Fatemi Ghomi, S.M.T. & Wilson, J.M. (2003). The capacitated lot sizing problem: a review of models and algorithms. Omega. 31(5), 365-378. DOI: http://dx.doi.org/ 10.1016/S0305-0483(03)00059-8.
  • [6] Jans, R. & Degraeve, Z. (2007). Meta-heuristics for dynamic lot sizing: a review and comparison of solution approaches. European Journal of Operational Research. 177, 1855-1875. DOI: 10.1016/j.ejor.2005.12.008.
  • [7] Guner, G., Tunali, H.S. & Jans, R. (2010). A review of applications of genetic algorithms in lot sizing. Journal of Intelligent Manufacturing. 21, 575-590. DOI: http://dx.doi.org/10.1007/s10845-008-0205-2.
  • [8] Kande, S., Prins, C., Belgacem, L. & Redon, B. (2015). Multi-start Iterated Local Search for two-echelon distribution network for perishable products. Proceedings of the International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES, 294-303. DOI: 10.5220/0005224902940303.
  • [9] Stützle, T. (1999). Iterated local search for the quadratic assignment problem, Technical Report AIDA-99-03. FG Intellektik. FB Informatik. TU Darmstadt.
  • [10] Lourenço, H.R., Martin, O. & Stützle, T. (2010). Iterated Local Search: Framework and Applications [in:] Handbook of Metaheuristics. Kluwer Academic Publishers.
Uwagi
PL
Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-d68e3482-a961-4ab7-9110-30207ac91be1
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