How to cite this paper
Chavarro, G., Fresen, M., González, E., Ferro, D & López-Ospina, H. (2021). Solving the one-warehouse N-retailers problem with stochastic demand: An inter-ratio policies approach.International Journal of Industrial Engineering Computations , 12(1), 131-142.
Refrences
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Abdul-Jalbar, B., Segerstedt, A., Sicilia, J., & Nilsson, A. (2010). A new heuristic to solve the one-warehouse N-retailer problem. Computers & Operations Research, 37(2), 265–272.
Andersson, J., & Marklund, J. (2000). Decentralized inventory control in a two-level distribution system. European Journal of Operational Research, 127(3), 483–506.
Bean, W. L., Joubert, J. W., & Luhandjula, M. K. (2016). Inventory management under uncertainty: A military application. Computers & Industrial Engineering, 96, 96–107.
Berling, P., & Marklund, J. (2014). Multi-echelon inventory control: an adjusted normal demand model for implementation in practice. International Journal of Production Research, 52(11), 3331–3347.
Carvajal, J., Castaño, F., Sarache, W., & Costa, Y. (2019). Heuristic approaches for a two-echelon constrained joint replenishment and delivery problem. International Journal of Production Economics.
Costantino, F., Di Gravio, G., Shaban, A., & Tronci, M. (2014). The impact of information sharing and inventory control coordination on supply chain performances. Computers & Industrial Engineering, 76, 292–306.
Disney, S. M., Maltz, A., Wang, X., & Warburton, R. D. H. (2016). Inventory management for stochastic lead times with order crossovers. European Journal of Operational Research, 248(2), 473–486.
Ercan, E. N., & Hakan, A. (2013). The one warehouse and N retailers problem with uncertain demand BT - Proceedings of the 2013 International Conference on Information, Business and Education Technology (ICIBET 2013). Atlantis Press.
Escuín, D., Polo, L., & Ciprés, D. (2017). On the comparison of inventory replenishment policies with time-varying stochastic demand for the paper industry. Journal of Computational and Applied Mathematics, 309, 424–434.
Fera, M., Fruggiero, F., Lambiase, A., Macchiaroli, R., & Miranda, S. (2017). The role of uncertainty in supply chains under dynamic modeling. International Journal of Industrial Engineering Computations, 8(1), 119–140.
Framinan, J. M., & Perez-Gonzalez, P. (2015). On heuristic solutions for the stochastic flowshop scheduling problem. European Journal of Operational Research, 246(2), 413–420.
Ghiami, Y., & Williams, T. (2015). A two-echelon production-inventory model for deteriorating items with multiple buyers. International Journal of Production Economics, 159, 233–240.
Guchhait, P., Maiti, M. K., & Maiti, M. (2014). Inventory policy of a deteriorating item with variable demand under trade credit period. Computers & Industrial Engineering, 76, 75–88.
Hoseini Shekarabi, S. A., Gharaei, A., & Karimi, M. (2019). Modelling and optimal lot-sizing of integrated multi-level multi-wholesaler supply chains under the shortage and limited warehouse space: generalised outer approximation. International Journal of Systems Science: Operations & Logistics, 6(3), 237–257.
Li, X., & Wang, Q. (2007). Coordination mechanisms of supply chain systems. European Journal of Operational Research, 179(1), 1–16.
Li, Y., & Liu, Y. (2019). A risk-averse multi-item inventory problem with uncertain demand. Journal of Data, Information and Management, 1(3), 77–90.
Liberopoulos, G., Tsikis, I., & Delikouras, S. (2010). Backorder penalty cost coefficient “b”: What could it be? International Journal of Production Economics, 123(1), 166–178.
Liu, F., & Song, J.-S. (2011). Good and Bad News About the (S, T) Policy. Manufacturing & Service Operations Management, 14(1), 42–49.
Morton, A. (2006). Structural properties of network revenue management models: An economic perspective. Naval Research Logistics (NRL), 53(8), 748–760.
Mousavi, S. M., Alikar, N., Niaki, S. T. A., & Bahreininejad, A. (2015). Optimizing a location allocation-inventory problem in a two-echelon supply chain network: A modified fruit fly optimization algorithm. Computers & Industrial Engineering, 87, 543–560.
Rodado, D., Escobar, J., García-Cáceres, R., & Atencio, F. (2017). A mathematical model for the product mixing and lot-sizing problem by considering stochastic demand. International Journal of Industrial Engineering Computations, 8(2), 237–250.
Roundy, R. (1985). 98%-Effective Integer-Ratio Lot-Sizing for One-Warehouse Multi-Retailer Systems. Management Science, 31(11), 1416–1430.
Schwarz, L. B. (1973). A Simple Continuous Review Deterministic One-Warehouse N-Retailer Inventory Problem. Management Science, 19(5), 555–566.
Shaban, A., Costantino, F., Di Gravio, G., & Tronci, M. (2019). A new efficient collaboration model for multi-echelon supply chains. Expert Systems with Applications, 128, 54–66.
Shekarian, E., Kazemi, N., Abdul-Rashid, S. H., & Olugu, E. U. (2017). Fuzzy inventory models: A comprehensive review. Applied Soft Computing, 55, 588–621.
Torkul, O., Yılmaz, R., Selvi, İ. H., & Cesur, M. R. (2016). A real-time inventory model to manage variance of demand for decreasing inventory holding cost. Computers & Industrial Engineering, 102, 435–439.
Tyworth, J. (2000). A note on solutions to the inventory model for gamma lead‐time demand. International Journal of Physical Distribution & Logistics Management, 30(6), 534–539.
Tyworth, J. E., & O’Neill, L. (1997). Robustness of the normal approximation of lead-time demand in a distribution setting. Naval Research Logistics (NRL), 44(2), 165–186.
Wang, Y., Ma, X., Liu, M., Gong, K., Liu, Y., Xu, M., & Wang, Y. (2017). Cooperation and profit allocation in two-echelon logistics joint distribution network optimization. Applied Soft Computing, 56, 143–157.
Zhao, S. T., Wu, K., & Yuan, X.-M. (2016). Optimal integer-ratio inventory coordination policy for an integrated multi-stage supply chain. Applied Mathematical Modelling, 40(5), 3876–3894.
Zissis, D., Ioannou, G., & Burnetas, A. (2020). Coordinating lot sizing decisions under bilateral information asymmetry. Production and Operations Management, 29(2), 371-387.
Abdul-Jalbar, B., Segerstedt, A., Sicilia, J., & Nilsson, A. (2010). A new heuristic to solve the one-warehouse N-retailer problem. Computers & Operations Research, 37(2), 265–272.
Andersson, J., & Marklund, J. (2000). Decentralized inventory control in a two-level distribution system. European Journal of Operational Research, 127(3), 483–506.
Bean, W. L., Joubert, J. W., & Luhandjula, M. K. (2016). Inventory management under uncertainty: A military application. Computers & Industrial Engineering, 96, 96–107.
Berling, P., & Marklund, J. (2014). Multi-echelon inventory control: an adjusted normal demand model for implementation in practice. International Journal of Production Research, 52(11), 3331–3347.
Carvajal, J., Castaño, F., Sarache, W., & Costa, Y. (2019). Heuristic approaches for a two-echelon constrained joint replenishment and delivery problem. International Journal of Production Economics.
Costantino, F., Di Gravio, G., Shaban, A., & Tronci, M. (2014). The impact of information sharing and inventory control coordination on supply chain performances. Computers & Industrial Engineering, 76, 292–306.
Disney, S. M., Maltz, A., Wang, X., & Warburton, R. D. H. (2016). Inventory management for stochastic lead times with order crossovers. European Journal of Operational Research, 248(2), 473–486.
Ercan, E. N., & Hakan, A. (2013). The one warehouse and N retailers problem with uncertain demand BT - Proceedings of the 2013 International Conference on Information, Business and Education Technology (ICIBET 2013). Atlantis Press.
Escuín, D., Polo, L., & Ciprés, D. (2017). On the comparison of inventory replenishment policies with time-varying stochastic demand for the paper industry. Journal of Computational and Applied Mathematics, 309, 424–434.
Fera, M., Fruggiero, F., Lambiase, A., Macchiaroli, R., & Miranda, S. (2017). The role of uncertainty in supply chains under dynamic modeling. International Journal of Industrial Engineering Computations, 8(1), 119–140.
Framinan, J. M., & Perez-Gonzalez, P. (2015). On heuristic solutions for the stochastic flowshop scheduling problem. European Journal of Operational Research, 246(2), 413–420.
Ghiami, Y., & Williams, T. (2015). A two-echelon production-inventory model for deteriorating items with multiple buyers. International Journal of Production Economics, 159, 233–240.
Guchhait, P., Maiti, M. K., & Maiti, M. (2014). Inventory policy of a deteriorating item with variable demand under trade credit period. Computers & Industrial Engineering, 76, 75–88.
Hoseini Shekarabi, S. A., Gharaei, A., & Karimi, M. (2019). Modelling and optimal lot-sizing of integrated multi-level multi-wholesaler supply chains under the shortage and limited warehouse space: generalised outer approximation. International Journal of Systems Science: Operations & Logistics, 6(3), 237–257.
Li, X., & Wang, Q. (2007). Coordination mechanisms of supply chain systems. European Journal of Operational Research, 179(1), 1–16.
Li, Y., & Liu, Y. (2019). A risk-averse multi-item inventory problem with uncertain demand. Journal of Data, Information and Management, 1(3), 77–90.
Liberopoulos, G., Tsikis, I., & Delikouras, S. (2010). Backorder penalty cost coefficient “b”: What could it be? International Journal of Production Economics, 123(1), 166–178.
Liu, F., & Song, J.-S. (2011). Good and Bad News About the (S, T) Policy. Manufacturing & Service Operations Management, 14(1), 42–49.
Morton, A. (2006). Structural properties of network revenue management models: An economic perspective. Naval Research Logistics (NRL), 53(8), 748–760.
Mousavi, S. M., Alikar, N., Niaki, S. T. A., & Bahreininejad, A. (2015). Optimizing a location allocation-inventory problem in a two-echelon supply chain network: A modified fruit fly optimization algorithm. Computers & Industrial Engineering, 87, 543–560.
Rodado, D., Escobar, J., García-Cáceres, R., & Atencio, F. (2017). A mathematical model for the product mixing and lot-sizing problem by considering stochastic demand. International Journal of Industrial Engineering Computations, 8(2), 237–250.
Roundy, R. (1985). 98%-Effective Integer-Ratio Lot-Sizing for One-Warehouse Multi-Retailer Systems. Management Science, 31(11), 1416–1430.
Schwarz, L. B. (1973). A Simple Continuous Review Deterministic One-Warehouse N-Retailer Inventory Problem. Management Science, 19(5), 555–566.
Shaban, A., Costantino, F., Di Gravio, G., & Tronci, M. (2019). A new efficient collaboration model for multi-echelon supply chains. Expert Systems with Applications, 128, 54–66.
Shekarian, E., Kazemi, N., Abdul-Rashid, S. H., & Olugu, E. U. (2017). Fuzzy inventory models: A comprehensive review. Applied Soft Computing, 55, 588–621.
Torkul, O., Yılmaz, R., Selvi, İ. H., & Cesur, M. R. (2016). A real-time inventory model to manage variance of demand for decreasing inventory holding cost. Computers & Industrial Engineering, 102, 435–439.
Tyworth, J. (2000). A note on solutions to the inventory model for gamma lead‐time demand. International Journal of Physical Distribution & Logistics Management, 30(6), 534–539.
Tyworth, J. E., & O’Neill, L. (1997). Robustness of the normal approximation of lead-time demand in a distribution setting. Naval Research Logistics (NRL), 44(2), 165–186.
Wang, Y., Ma, X., Liu, M., Gong, K., Liu, Y., Xu, M., & Wang, Y. (2017). Cooperation and profit allocation in two-echelon logistics joint distribution network optimization. Applied Soft Computing, 56, 143–157.
Zhao, S. T., Wu, K., & Yuan, X.-M. (2016). Optimal integer-ratio inventory coordination policy for an integrated multi-stage supply chain. Applied Mathematical Modelling, 40(5), 3876–3894.
Zissis, D., Ioannou, G., & Burnetas, A. (2020). Coordinating lot sizing decisions under bilateral information asymmetry. Production and Operations Management, 29(2), 371-387.