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Integrating meta-heuristics, simulation and exact techniques for production planning of a failure-prone manufacturing system

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  • Diaz, Juan Esteban
  • Handl, Julia
  • Xu, Dong-Ling

Abstract

This paper considers a real-world production planning problem in which production line failures cause uncertainty regarding the practical implementation of a given production plan. We provide a general formulation of this problem as an extended stochastic knapsack problem, in which uncertainty arises from non-trivial perturbations to the decision variables that cannot be represented in closed form.

Suggested Citation

  • Diaz, Juan Esteban & Handl, Julia & Xu, Dong-Ling, 2018. "Integrating meta-heuristics, simulation and exact techniques for production planning of a failure-prone manufacturing system," European Journal of Operational Research, Elsevier, vol. 266(3), pages 976-989.
    • Handle: RePEc:eee:ejores:v:266:y:2018:i:3:p:976-989
    DOI: 10.1016/j.ejor.2017.10.062
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    1. Perboli, Guido & Tadei, Roberto & Gobbato, Luca, 2014. "The Multi-Handler Knapsack Problem under Uncertainty," European Journal of Operational Research, Elsevier, vol. 236(3), pages 1000-1007.
    2. Li, Jianzhi & González, Miguel & Zhu, Yun, 2009. "A hybrid simulation optimization method for production planning of dedicated remanufacturing," International Journal of Production Economics, Elsevier, vol. 117(2), pages 286-301, February.
    3. Balev, Stefan & Yanev, Nicola & Freville, Arnaud & Andonov, Rumen, 2008. "A dynamic programming based reduction procedure for the multidimensional 0-1 knapsack problem," European Journal of Operational Research, Elsevier, vol. 186(1), pages 63-76, April.
    4. Chen, Kai & Ross, Sheldon M., 2014. "An adaptive stochastic knapsack problem," European Journal of Operational Research, Elsevier, vol. 239(3), pages 625-635.
    5. Wilbaut, Christophe & Salhi, Saïd & Hanafi, Saïd, 2009. "An iterative variable-based fixation heuristic for the 0-1 multidimensional knapsack problem," European Journal of Operational Research, Elsevier, vol. 199(2), pages 339-348, December.
    6. Hadar, Josef & Russell, William R, 1969. "Rules for Ordering Uncertain Prospects," American Economic Review, American Economic Association, vol. 59(1), pages 25-34, March.
    7. Gansterer, Margaretha & Almeder, Christian & Hartl, Richard F., 2014. "Simulation-based optimization methods for setting production planning parameters," International Journal of Production Economics, Elsevier, vol. 151(C), pages 206-213.
    8. Kataoka, Seiji & Yamada, Takeo, 2014. "Upper and lower bounding procedures for the multiple knapsack assignment problem," European Journal of Operational Research, Elsevier, vol. 237(2), pages 440-447.
    9. Almeder, Christian & Hartl, Richard F., 2013. "A metaheuristic optimization approach for a real-world stochastic flexible flow shop problem with limited buffer," International Journal of Production Economics, Elsevier, vol. 145(1), pages 88-95.
    10. Villegas, Juan G. & Prins, Christian & Prodhon, Caroline & Medaglia, Andrés L. & Velasco, Nubia, 2013. "A matheuristic for the truck and trailer routing problem," European Journal of Operational Research, Elsevier, vol. 230(2), pages 231-244.
    11. Byrne, M. D. & Bakir, M. A., 1999. "Production planning using a hybrid simulation - analytical approach," International Journal of Production Economics, Elsevier, vol. 59(1-3), pages 305-311, March.
    12. Shi, Xiutian & Shen, Houcai & Wu, Ting & Cheng, T.C.E., 2014. "Production planning and pricing policy in a make-to-stock system with uncertain demand subject to machine breakdowns," European Journal of Operational Research, Elsevier, vol. 238(1), pages 122-129.
    13. Gnoni, M. G. & Iavagnilio, R. & Mossa, G. & Mummolo, G. & Di Leva, A., 2003. "Production planning of a multi-site manufacturing system by hybrid modelling: A case study from the automotive industry," International Journal of Production Economics, Elsevier, vol. 85(2), pages 251-262, August.
    14. Vaurio, Jussi K. & Jänkälä, Kalle E., 2006. "Evaluation and comparison of estimation methods for failure rates and probabilities," Reliability Engineering and System Safety, Elsevier, vol. 91(2), pages 209-221.
    15. A. Charnes & W. W. Cooper, 1959. "Chance-Constrained Programming," Management Science, INFORMS, vol. 6(1), pages 73-79, October.
    16. García-Martínez, C. & Rodriguez, F.J. & Lozano, M., 2014. "Tabu-enhanced iterated greedy algorithm: A case study in the quadratic multiple knapsack problem," European Journal of Operational Research, Elsevier, vol. 232(3), pages 454-463.
    17. Yamada, Takeo & Takeoka, Takahiro, 2009. "An exact algorithm for the fixed-charge multiple knapsack problem," European Journal of Operational Research, Elsevier, vol. 192(2), pages 700-705, January.
    18. Gomes, A. Miguel & Oliveira, Jose F., 2006. "Solving Irregular Strip Packing problems by hybridising simulated annealing and linear programming," European Journal of Operational Research, Elsevier, vol. 171(3), pages 811-829, June.
    19. Kim, Bokang & Kim, Sooyoung, 2001. "Extended model for a hybrid production planning approach," International Journal of Production Economics, Elsevier, vol. 73(2), pages 165-173, September.
    20. Byrne, M.D. & Hossain, M.M., 2005. "Production planning: An improved hybrid approach," International Journal of Production Economics, Elsevier, vol. 93(1), pages 225-229, January.
    21. Arakawa, Masahiro & Fuyuki, Masahiko & Inoue, Ichiro, 2003. "An optimization-oriented method for simulation-based job shop scheduling incorporating capacity adjustment function," International Journal of Production Economics, Elsevier, vol. 85(3), pages 359-369, September.
    22. David Pisinger, 2000. "A Minimal Algorithm for the Bounded Knapsack Problem," INFORMS Journal on Computing, INFORMS, vol. 12(1), pages 75-82, February.
    23. Chen, Yuning & Hao, Jin-Kao, 2014. "A “reduce and solve” approach for the multiple-choice multidimensional knapsack problem," European Journal of Operational Research, Elsevier, vol. 239(2), pages 313-322.
    24. Brian C. Dean & Michel X. Goemans & Jan Vondrák, 2008. "Approximating the Stochastic Knapsack Problem: The Benefit of Adaptivity," Mathematics of Operations Research, INFORMS, vol. 33(4), pages 945-964, November.
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    Cited by:

    1. Diaz, Juan Esteban & López-Ibáñez, Manuel, 2021. "Incorporating decision-maker’s preferences into the automatic configuration of bi-objective optimisation algorithms," European Journal of Operational Research, Elsevier, vol. 289(3), pages 1209-1222.
    2. Martello, Silvano & Monaci, Michele, 2020. "Algorithmic approaches to the multiple knapsack assignment problem," Omega, Elsevier, vol. 90(C).
    3. Homsi, Gabriel & Jordan, Jeremy & Martello, Silvano & Monaci, Michele, 2021. "The assignment and loading transportation problem," European Journal of Operational Research, Elsevier, vol. 289(3), pages 999-1007.
    4. Stefka Fidanova & Krassimir Todorov Atanassov, 2021. "ACO with Intuitionistic Fuzzy Pheromone Updating Applied on Multiple-Constraint Knapsack Problem," Mathematics, MDPI, vol. 9(13), pages 1-7, June.

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