Stochastic Optimization of a Vendor-Managed Inventory Problem in a Two-Echelon Supply Chain
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Stochastic Optimization of a Vendor-Managed Inventory Problem in a Two-Echelon Supply Chain

Authors: Bita Payami-Shabestari, Dariush Eslami

Abstract:

The purpose of this paper is to develop a multi-product economic production quantity model under vendor management inventory policy and restrictions including limited warehouse space, budget, and number of orders, average shortage time and maximum permissible shortage. Since the “costs” cannot be predicted with certainty, it is assumed that data behave under uncertain environment. The problem is first formulated into the framework of a bi-objective of multi-product economic production quantity model. Then, the problem is solved with three multi-objective decision-making (MODM) methods. Then following this, three methods had been compared on information on the optimal value of the two objective functions and the central processing unit (CPU) time with the statistical analysis method and the multi-attribute decision-making (MADM). The results are compared with statistical analysis method and the MADM. The results of the study demonstrate that augmented-constraint in terms of optimal value of the two objective functions and the CPU time perform better than global criteria, and goal programming. Sensitivity analysis is done to illustrate the effect of parameter variations on the optimal solution. The contribution of this research is the use of random costs data in developing a multi-product economic production quantity model under vendor management inventory policy with several constraints.

Keywords: Economic production quantity, random cost, supply chain management, vendor-managed inventory.

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[1] Nakhjirkan, S., & Mokhatab Rafiei, F. An integrated multi-echelon supply chain network design considering stochastic demand: a genetic algorithm-based solution. PROMET-Traffic & Transportation, 29(4), 391-400(2017).
[2] Olugu, E. U., & Wong, K. Y. Supply chain performance evaluation: trends and challenges (2009).
[3] Harris, J. A. On the calculation of intra-class and inter-class coefficients of correlation from class moments when the number of possible combinations is large. Biometrika, 9(3/4), 446-472(2009).
[4] Pentico, D. W., & Drake, M. J. A survey of deterministic models for the EOQ and EPQ with partial backordering. European Journal of Operational Research, 214(2), 179-198(2011).
[5] Björk, M.K. The economic production quantity problem with a finite production rate and fuzzy cycle time. Proceeding Soft he 41 st Hawaii International Conference on System Sciences (2008).
[6] Nobil, A. H., Sedigh, A. H. A., & Cárdenas-Barrón, L. E. A multi-machine multi-product EPQ problem for an imperfect manufacturing system considering utilization and allocation decisions. Expert Systems with Applications, 56, 310-319(2016).
[7] Sadeghi, J., Niaki, S. T. A., Malekian, M. R., & Wang, Y. A Lagrangian relaxation for a fuzzy random EPQ problem with shortages and redundancy allocation: two tuned meta-heuristics. International Journal of Fuzzy Systems, 20(2), 515-533(2018).
[8] Karbassi Yazdi, A., Kaviani, M. A., Sarfaraz, A. H., Cárdenas-Barrón, L. E., Wee, H. M., & Tiwari, S. A comparative study on economic production quantity (EPQ) model under space constraint with different kinds of data. Grey Systems: Theory and Application, 9(1), 86-100(2019).
[9] Kundu, A., Guchhait, P., Das, B., & Maiti, M. A Multi-item EPQ Model with Variable Demand in an Imperfect Production Process. In Information Technology and Applied Mathematics, 217-233(2019).
[10] Gharaei, A., Hoseini Shekarabi, S. A., & Karimi, M. Modelling and optimal lot-sizing of the replenishments in constrained, multi-product and bi-objective EPQ models with defective products: Generalised Cross Decomposition. International Journal of Systems Science: Operations & Logistics, 1-13(2019).
[11] Guan, R., & Zhao, X. On contracts for VMI program with continuous review (r, Q) policy. European Journal of Operational Research, 207(2), 656-667(2010).
[12] Karimi, M., & Niknamfar, A. H. A vendor-managed inventory system considering the redundancy allocation problem and carbon emissions. International Journal of Management Science and Engineering Management, 12(4), 269-279(2017).
[13] Mokhtari, H., & Rezvan, M. T. A single-supplier, multi-buyer, multi-product VMI production-inventory system under partial backordering. Operational Research, 1–21(2017).
[14] Sadeghi, J., & Niaki, S. T. A. Two parameter tuned multi-objective evolutionary algorithms for a bi-objective vendor managed inventory model with trapezoidal fuzzy demand. Applied Soft Computing, 30, 567-576(2015).
[15] Sadeghi, J. A multi-item integrated ilers in a two-echelon supply chain management: a tuned-parameters hybrid meta-heuristic. Opsearch, 52(4), 631–649(2015).
[16] Darwish, M. A., & Odah, O. M. Vendor managed inventory model for single-vendor multi-retailer supply chains. European Journal of Operational Research, 204(3), 473-484(2010).
[17] Pasandideh, S. H. R., Niaki, S. T. A., & Nia, A. R. A genetic algorithm for vendor managed inventory control system of multi-product multi-constraint economic order quantity model. Expert Systems with Applications, 38(3), 2708-2716(2011).
[18] Cárdenas-Barrón, L. E., Treviño-Garza, G., & Wee, H. M. A simple and better algorithm to solve the vendor managed inventory control system of multi-product multi-constraint economic order quantity model. Expert Systems with Applications, 39(3), 3888-3895(2012).
[19] Kristianto, Y., Helo, P., Jiao, J. R., & Sandhu, M. Adaptive fuzzy vendor managed inventory control for mitigating the Bullwhip effect in supply chains. European Journal of Operational Research, 216(2), 346-355(2012).
[20] Yu, Y., Wang, Z., & Liang, L. A vendor managed inventory supply chain with deteriorating raw materials and products. International Journal of Production Economics, 136(2), 266-274(2012).
[21] Hariga, M., Gumus, M., Daghfous, A., & Goyal, S. K. A vendor managed inventory model under contractual storage agreement. Computers & Operations Research, 40(8), 2138-2144(2013).
[22] Mateen, A., & Chatterjee, A. K. Vendor managed inventory for single-vendor multi-retailer supply chains. Decision Support Systems, 70, 31-41(2013).
[23] Pasandideh, S. H. R., Niaki, S. T. A., & Far, M. H. Optimization of vendor managed inventory of multiproduct EPQ model with multiple constraints using genetic algorithm. The International Journal of Advanced Manufacturing Technology, 71(1-4), 365-376(2014).
[24] Nia, A. R., Far, M. H., & Niaki, S. T. A. A fuzzy vendor managed inventory of multi-item economic order quantity model under shortage: An ant colony optimization algorithm. International Journal of Production Economics, 155, 259-271(2014).
[25] Du, Y., Xie, L., Liu, J., Wang, Y., Xu, Y., & Wang, S. Multi-objective optimization of reverse osmosis networks by lexicographic optimization and augmented epsilon constraint method. Desalination, 333(1), 66–81(2014).
[26] Nia, A. R., Far, M. H., & Niaki, S. T. A. A hybrid genetic and imperialist competitive algorithm for green vendor managed inventory of multi-item multi-constraint EOQ model under shortage. Applied Soft Computing, 30, 353-364(2015).
[27] Lee, J. Y., Cho, R. K., & Paik, S. K. Supply chain coordination in vendor-managed inventory systems with stockout-cost sharing under limited storage capacity. European Journal of Operational Research, 248(1), 95-106(2016).
[28] Pasandideh, S. H. R., Niaki, S. T. A., & Ahmadi, P. Vendor-managed inventory in the joint replenishment problem of a multi-product single-supplier multiple-retailer supply chain: A teacher-learner-based optimization algorithm. Journal of Modelling in Management, 13(1), 156-178(2018).
[29] Zuanetti Filho, J., Dias, F., & Moura, A. Application of a vendor managed inventory (VMI) system model in an animal nutrition industry. Procedia CIRP, 67, 528-533(2018).
[30] Hariga, M., Babekian, S., & Bahroun, Z. Operational and environmental decisions for a two-stage supply chain under vendor managed consignment inventory partnership. International Journal of Production Research, 1-21(2018).
[31] Taylor, D. H. Global cases in logistics and supply chain management. Cengage Learning EMEA (1997).
[32] Chakraborty, S., Zavadskas, E.K. Applications of WASPAS method in manufacturing decision making, Informatica, 25(1), 1-20(2004).
[33] Razemi, J. Rad, R.H., Sangari, M.S. Developing a two-echelon mathematical model for a vendor-managed inventory (VMI) system. International Journal of Advanced Manufacturing Technology inventory model with different replenishment frequencies of reta8 (5–8), 773–783(2010).