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Optimising safety stock placement and lead time in an assembly supply chain using bi-objective MAX–MIN ant system

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  • Moncayo-Martínez, Luis A.
  • Zhang, David Z.
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    Abstract

    The problem of placing safety inventory over a network, which assembles a product, is a challenging issue in supply chain design (SCD) because manufacturers always want to reduce inventory all over the supply chain (SC). Moreover, the process of designing a SC and then placing inventory, to offer high service level at the lowest possible cost, across a complex SC, is not an easy task for decision makers. In this paper we use the SC representation proposed by Graves and Willems (2000), Manufacturing & Service Operations Management 2 (1), 68–83, where a SC is divided into many supplying, manufacturing, and delivering stages. Our problem is to select one resource option to perform each stage, and based on the selected options to place an amount of inventory (in-progress and on-hand) at each stage, in order to offer a satisfactory customer service level with as low as possible total supply chain cost. A resource option here represents a supplier, a manufacturing plant (production line), or a transport mode in a supplying, manufacturing, or delivering stage, respectively. We developed an approach based on ant colony optimisation (ACO) to minimise simultaneously the total supply chain cost and the products’ lead time to ensure product deliveries without delays. What are new in our approach are the bi-objective function and the computational efficiency of our ACO-based approach. In addition, ACO has not been applied to solve the inventory placement problem. As a validation of the model, we: (a) describe a successful application at CIFUNSA, one of the largest iron foundry in the world, and (b) compare different CPU time instances and metrics about multi-objective optimisation.

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    Bibliographic Info

    Article provided by Elsevier in its journal International Journal of Production Economics.

    Volume (Year): 145 (2013)
    Issue (Month): 1 ()
    Pages: 18-28

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    Handle: RePEc:eee:proeco:v:145:y:2013:i:1:p:18-28

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    Web page: http://www.elsevier.com/locate/ijpe

    Related research

    Keywords: Supply chain design; Safety stock placement; Multi-objective optimisation; Ant colony; Meta-heuristics;

    References

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    1. Sean P. Willems, 2008. "Data Set--Real-World Multiechelon Supply Chains Used for Inventory Optimization," Manufacturing & Service Operations Management, INFORMS, vol. 10(1), pages 19-23, February.
    2. Doerner, K.F. & Gutjahr, W.J. & Hartl, R.F. & Strauss, C. & Stummer, C., 2006. "Pareto ant colony optimization with ILP preprocessing in multiobjective project portfolio selection," European Journal of Operational Research, Elsevier, vol. 171(3), pages 830-841, June.
    3. Wang, Juite & Shu, Yun-Feng, 2007. "A possibilistic decision model for new product supply chain design," European Journal of Operational Research, Elsevier, vol. 177(2), pages 1044-1061, March.
    4. Spitter, J. M. & Hurkens, C. A. J. & de Kok, A. G. & Lenstra, J. K. & Negenman, E. G., 2005. "Linear programming models with planned lead times for supply chain operations planning," European Journal of Operational Research, Elsevier, vol. 163(3), pages 706-720, June.
    5. Gravel, Marc & Price, Wilson L. & Gagne, Caroline, 2002. "Scheduling continuous casting of aluminum using a multiple objective ant colony optimization metaheuristic," European Journal of Operational Research, Elsevier, vol. 143(1), pages 218-229, November.
    6. Melo, M.T. & Nickel, S. & Saldanha-da-Gama, F., 2009. "Facility location and supply chain management - A review," European Journal of Operational Research, Elsevier, vol. 196(2), pages 401-412, July.
    7. Gunasekaran, Angappa & Lai, Kee-hung & Edwin Cheng, T.C., 2008. "Responsive supply chain: A competitive strategy in a networked economy," Omega, Elsevier, vol. 36(4), pages 549-564, August.
    8. Paul Glasserman & Sridhar Tayur, 1995. "Sensitivity Analysis for Base-Stock Levels in Multiechelon Production-Inventory Systems," Management Science, INFORMS, vol. 41(2), pages 263-281, February.
    9. Stephen C. Graves & Sean P. Willems, 2005. "Optimizing the Supply Chain Configuration for New Products," Management Science, INFORMS, vol. 51(8), pages 1165-1180, August.
    10. Chopra, Sunil, 2003. "Designing the distribution network in a supply chain," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 39(2), pages 123-140, March.
    11. Persona, Alessandro & Battini, Daria & Manzini, Riccardo & Pareschi, Arrigo, 2007. "Optimal safety stock levels of subassemblies and manufacturing components," International Journal of Production Economics, Elsevier, vol. 110(1-2), pages 147-159, October.
    12. Doerner, K.F. & Gutjahr, W.J. & Hartl, R.F. & Strauss, C. & Stummer, C., 2008. "Nature-inspired metaheuristics for multiobjective activity crashing," Omega, Elsevier, vol. 36(6), pages 1019-1037, December.
    13. Osman, Hany & Demirli, Kudret, 2012. "Integrated safety stock optimization for multiple sourced stockpoints facing variable demand and lead time," International Journal of Production Economics, Elsevier, vol. 135(1), pages 299-307.
    14. Amini, Mehdi & Li, Haitao, 2011. "Supply chain configuration for diffusion of new products: An integrated optimization approach," Omega, Elsevier, vol. 39(3), pages 313-322, June.
    15. Stephen C. Graves & Sean P. Willems, 2000. "Optimizing Strategic Safety Stock Placement in Supply Chains," Manufacturing & Service Operations Management, INFORMS, vol. 2(1), pages 68-83, June.
    16. Moncayo-Martínez, Luis A. & Zhang, David Z., 2011. "Multi-objective ant colony optimisation: A meta-heuristic approach to supply chain design," International Journal of Production Economics, Elsevier, vol. 131(1), pages 407-420, May.
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