Optimizing Inventory Management Costs in Supply Chains by Determining Safety Stock Placement
الموضوعات :
1 - Department of Industrial Engineering, Babol Noshirvani University of Technology, Babol, Iran
الکلمات المفتاحية: Optimization Algorithms, Supply chains, Network problems, Safety stock,
ملخص المقالة :
For a production business, the measurement of safety inventory to be maintained during each step of a supply chain is a key concern and requires providing the clients an irregular state of management. The stock held should be small to reduce holding costs and capacity while maintaining the capacity to service customers in time to satisfy much, if not all, the demand. This paper discusses this issue by using a deterministic time structure and provides a measure of the security position of stock in supply chains for the overall network. First, prove that the overall problem is NP-hard. Then set up a couple of parameters that characterize an optimal overall network structure. To take care of these problems, a polynomial approximation is considered. An arrangement of computational tests to survey the execution of the general-network calculation and to decide how to set different parameters for the calculation is selected. In addition to the general network case, the two-layer network issues are considered. Also, a nonlinear model for determining the level of safety stock in different components of the supply chain to minimize the related safety stock costs is developed.
Amirjabbari, B., & Bhuiyan, N. (2014). Determining supply chain safety stock level and location. Journal of Industrial Engineering and Management (JIEM), 7(1), 42-71.
Axater, S. (2000). Inventory control. In: Kluwer Academic Publishers, Boston, MA.Ballou, R. H. (2007). Business logistics/supply chain management: planning, organizing, and controlling the supply chain: Pearson Education India.
Benson, H. P. (1995). Concave minimization: theory, applications and algorithms. In (pp. 43-148): Springer.
Benson, H. P. (1996). Deterministic algorithms for constrained concave minimization: A unified critical survey. Naval Research Logistics (NRL), 43(6), 765-795.
Chopra, S., & Meindl, P. (2007). Supply chain management. Strategy, planning & operation. In Das summa summarum des management (pp. 265-275):Springer.
Fakhrzad, M., & Goodarzian, F. (2021). A new multiobjective mathematical model for a Citrus supply chain network design: Metaheuristic algorithms. Journal of Optimization in Industrial Engineering, 14(2), 127-144.
Gonçalves, J. N., Carvalho, M. S., & Cortez, P. (2020). Operations research models and methods for safety stock determination: A review. Operations Research Perspectives, 100164.
Graves, S. C. (1985). A multi-echelon inventory model for a repairable item with one-for-one replenishment. Management science, 31(10), 1247-1256.
Graves, S. C., & Willems, S. P. (2003). Supply chain design: safety stock placement and supply chain configuration. Handbooks in operations research and management science, 11, 95-132.
Horst, R. (1984). On the global minimization of concave functions. Operations-Research-Spektrum, 6(4), 195-205.
Karim, M. A., Samaranayake, P., Smith, A., & Halgamuge, S. K. (2010). An on-time delivery improvement model for anufacturing organisations. International Journal of Production Research, 48(8), 2373-2394.
Korte, B., & Vygen, J. (2005). Combinatorial optimization. Theory and algorithms. 2000. Cited on, 84-84.
Lee, H. L., & Billington, C. (1995). The evolution of supply-chain-management models and practice at Hewlett-Packard. Interfaces, 25(5), 42-63.
Magnanti, T. L., Shen, Z.-J. M., Shu, J., Simchi-Levi, D., & Teo, C.-P. (2006). Inventory placement in acyclic supply chain networks. Operations Research Letters, 34(2), 228-238.
Maia, L. O. A., & Qassim, R. Y. (1999). Minimum cost safety stocks for frequent delivery manufacturing. International Journal of Production Economics, 62(3), 233-236.
Minner, S. (2003). Multiple-supplier inventory models in supply chain management: A review. International Journal of Production Economics, 81, 265-279.
Minner, S. (2012). Strategic safety stocks in supply chains (Vol. 490): Springer Science & Business Media. Ngubia, L. W. (2018). Extent of Application of Various Inventory Control Techniques Among Supermarkets In Nairobi. International Journal of Business Management and Processes (ISSN 2616-3209), 2(2), 6-6.
Pardalos, P. M., & Rosen, J. B. (1986). Methods for global concave minimization: A bibliographic survey. Siam Review, 28(3), 367-379.
Persona, A., Battini, D., Manzini, R., & Pareschi, A. (2007). Optimal safety stock levels of subassemblies and manufacturing components. International Journal of Production Economics, 110(1-2), 147-159.
Sadeghi, J., Sadeghi, A., & Saidi Mehrabad, M. (2011). A parameter-tuned genetic algorithm for vendor managed inventory model for a case single-vendor single-retailer with multi-product and multi-constraint. Journal of Optimization in Industrial Engineering(9), 57-67.
Sahebjamnia, N., Goodarzian, F., & Hajiaghaei-Keshteli, M. (2020). Optimization of multi-period three-echelon citrus supply chain problem. Journal of Optimization in Industrial Engineering, 13(1), 39-53.
Sahni, S. (1974). Computationally Related Problems. SIAM Journal on Computing, 3(4), 262-279. doi:10.1137/0203021
Stenross, F. M., & Sweet, G. J. (1991). Implementing an integrated supply chain. Paper presented at the Annual conference proceedings.
Vavasis, S. A. (1990). Quadratic programming is in NP. Information Processing Letters, 36(2), 73-77. doi:10.1016/0020-0190(90)90100-C
Zhao, X., Lai, F., & Lee, T. (2001). Evaluation of safety stock methods in multilevel material requirements planning (MRP) systems. Production Planning & Control, 12(8), 794-803.
Zimmerman, H.-J. (1983). Using fuzzy sets in operational research. European Journal of Operational Research, 13(3), 201-216.