An inventory position-based policy for better supply chain performance

References

• Silver EA, Pyke DF, Peterson R. Inventory management and production planning and scheduling. New York (NY): Wiley; 1998.
   Google Scholar
• Sensi GD, Longo F, Mirabelli G. Inventory policies analysis under demand patterns and lead times constraints in a real supply chain. Int J Prod Res. 2008;46:6997–7016.10.1080/00207540701528776
   Web of Science ®Google Scholar
• Lau RSM, Xie J, Zhao X. Effect of inventory policy on supply chain performance: a simulation study of critical decision parameters. Comput Ind Eng. 2008;55:620–633.10.1016/j.cie.2008.02.002
   Web of Science ®Google Scholar
• Liang WY, Huang CC. Agent-based demand forecast in multi-echelon supply chain. Decis Support Syst. 2006;42:390–407.10.1016/j.dss.2005.01.009
   Web of Science ®Google Scholar
• Boute RN, Disney SM, Lambrecht MR, et al. Designing replenishment rules in a two-echelon supply chain with a flexible or an inflexible capacity strategy. Int J Prod Econ. 2009;119:187–198.10.1016/j.ijpe.2009.01.012
   Web of Science ®Google Scholar
• Paul B, Rajendran C. Optimal and heuristic base-stock levels and rationing policy for a divergent supply chain. Int J Ind Syst Eng. 2010;5:460–484.10.1504/IJISE.2010.032967
   Google Scholar
• Li Q, Disney SM, Gaalman G. Avoiding the bullwhip effect using damped trend forecasting and the order-up-to replenishment policy. Int J Prod Econ. 2014;149:3–16.10.1016/j.ijpe.2013.11.010
   Web of Science ®Google Scholar
• Dejonckheere J, Disney SM, Lambrecht MR, et al. Measuring and avoiding the bullwhip effect: a control theoretic approach. Eur J Oper Res. 2003;147:567–590.10.1016/S0377-2217(02)00369-7
   Web of Science ®Google Scholar
• Dejonckheere J, Disney SM, Lambrecht MR, et al. The impact of information enrichment on the bullwhip effect in supply chains: a control engineering perspective. Eur J Oper Res. 2004;153:727–750.10.1016/S0377-2217(02)00808-1
   Web of Science ®Google Scholar
• Cannella S, Ciancimino E. On the bullwhip avoidance phase: supply chain collaboration and order smoothing. Int J Prod Res. 2010;48:6739–6776.10.1080/00207540903252308
   Web of Science ®Google Scholar
• Love SF. Inventory control. New York (NY): McGraw-Hill; 1979.
   Google Scholar
• Kelle P, Milne A. The effect of (s, S) ordering policy on the supply chain. Int J Prod Econ. 1999;59:113–122.10.1016/S0925-5273(98)00232-1
   Web of Science ®Google Scholar
• Lee HT, Wu JC. A study on inventory replenishment policies in a two-echelon supply chain system. Comput Ind Eng. 2006;51:257–263.10.1016/j.cie.2006.01.005
   Web of Science ®Google Scholar
• Disney SM, Towill DR. A methodology for benchmarking replenishment-induced bullwhip. Supply Chain Manage Int J. 2006;11:160–168.10.1108/13598540610652555
   Web of Science ®Google Scholar
• Chatfield DC, Kim JG, Harrison TP, et al. The bullwhip effect-impact of stochastic lead time, information quality, and information sharing: a simulation study. Prod Oper Manage. 2004;13:340–353.
   Web of Science ®Google Scholar
• Chen F, Ryan JK, Simchi-Levi D. The impact of exponential smoothing forecasts on the bullwhip effect. Nav Res Logist. 2000a;47:271–286.
   Web of Science ®Google Scholar
• Chen F, Drezner Z, Ryan JK, et al. Quantifying the bullwhip effect in a supply chain: the impact of forecasting, lead time and information. Manage Sci. 2000b;46:436–443.10.1287/mnsc.46.3.436.12069
   Web of Science ®Google Scholar
• Daniel JSR, Rajendran C. A simulation-based genetic algorithm for inventory optimization in a serial supply chain. Int Trans Oper Res. 2005;12:101–127.10.1111/itor.2005.12.issue-1
   Google Scholar
• Dominguez R, Framinan JM, Cannella S. Serial vs. divergent supply chain networks: a comparative analysis of the bullwhip effect. Int J Prod Res. 2013;52:2194–2210.
   Web of Science ®Google Scholar
• Dominguez R, Cannella S, Framinan JM. On bullwhip-limiting strategies in divergent supply chain networks. Comput Ind Eng. 2014;73:85–95.10.1016/j.cie.2014.04.008
   Web of Science ®Google Scholar
• Pillai VM, Pamulety TC, Elluri PV. Performance analysis of some supply chain replenishment strategies. Int J Logist Res Appl. 2013;17:357–376.
   Web of Science ®Google Scholar
• Wadhwa S, Bibhushan, Chan FTS. Inventory performance of some supply chain inventory policies under impulse demand. Int J Prod Res. 2009;47:3307–3332.10.1080/00207540701689750
   Web of Science ®Google Scholar
• Chan FTS, Prakash A. Inventory management in a lateral collaborative manufacturing supply chain: a simulation study. Int J Prod Res. 2012;50:4670–4685.10.1080/00207543.2011.628709
   Web of Science ®Google Scholar
• Monthatipkul C, Yenradee P. Inventory/distribution control system in a one-warehouse/multi-retailer supply chain. Int J Prod Econ. 2008;114:119–133.10.1016/j.ijpe.2007.12.010
   Web of Science ®Google Scholar
• Andersson J, Marklund J. Decentralized inventory control in a two-level distribution system. Eur J Oper Res. 2000;127:483–506.10.1016/S0377-2217(99)00332-X
   Web of Science ®Google Scholar
• Disney SM, Grubbström RW. Economic consequences of a production and inventory control policy. Int J Prod Res. 2004;42:3419–3431.10.1080/00207540410001727640
   Web of Science ®Google Scholar
• Pfohl HC, Cullmann O, Stolzle W. Inventory management with statistical process control: simulation and evaluation. J Bus Logist. 1999;20:101–120.
   Google Scholar
• Costantino F, Gravio GD, Shaban A, et al. A real-time SPC inventory replenishment system to improve supply chain performances. Expert Syst Appl. 2015a;42:1665–1683.10.1016/j.eswa.2014.09.028
   Web of Science ®Google Scholar
• Costantino F, Gravio GD, Shaban A, et al. SPC forecasting system to mitigate the bullwhip effect and inventory variance in supply chains. Expert Syst Appl. 2015b;42:1773–1787.10.1016/j.eswa.2014.09.039
   Web of Science ®Google Scholar
• Disney SM, Towill DR. Eliminating drift in inventory and order based production control systems. Int J Prod Econ. 2005;93–94:331–344.10.1016/j.ijpe.2004.06.031
   Web of Science ®Google Scholar
• Disney SM, Towill DR, Velde WVD. Variance amplification and the golden ratio in production and inventory control. Int J Prod Econ. 2004;90:295–309.10.1016/j.ijpe.2003.10.009
   Web of Science ®Google Scholar
• Sezen B, Kitapci H. Spreadsheet simulation for the supply chain inventory problem. Prod Plann Control. 2007;18:9–15.10.1080/09537280600940622
   Web of Science ®Google Scholar
• Jakšič M, Rusjan B. The effect of replenishment policies on the bullwhip effect: a transfer function approach. Eur J Oper Res. 2008;184:946–961.
   Web of Science ®Google Scholar
• Kelepouris T, Miliotis P, Pramatari K. The impact of replenishment parameters and information sharing on the bullwhip effect: a computational study. Comput Oper Res. 2008;35:3657–3670.10.1016/j.cor.2007.04.004
   Web of Science ®Google Scholar
• Zhao X, Xie J. Forecasting errors and the value of information sharing in a supply chain. Int J Prod Res. 2002;40:311–335.10.1080/00207540110079121
   Web of Science ®Google Scholar
• Chaharsooghi SK, Heydari J. LT variance or LT mean reduction in supply chain management: which one has a higher impact on SC performance? Int J Prod Econ. 2010;124:475–481.10.1016/j.ijpe.2009.12.010
   Web of Science ®Google Scholar
• Movahed KK, Zhang Z. Robust design of (s, S) inventory policy parameters in supply chains with demand and lead time uncertainties. Int J Syst Sci. 2015;46:2258–2268.10.1080/00207721.2013.860637
   Web of Science ®Google Scholar
• Cachon GP, Fisher M. Supply chain inventory management and the value of shared information. Manage Sci. 2000;46:1032–1048.10.1287/mnsc.46.8.1032.12029
   Web of Science ®Google Scholar
• Christopher M, Lee H. Mitigating supply chain risk through improved confidence. Int J Phys Distrib Logist Manage. 2004;34:388–396.10.1108/09600030410545436
   Google Scholar
• Bottani E, Montanari R. Supply chain design and cost analysis through simulation. Int J Prod Res. 2010;48:2859–2886.10.1080/00207540902960299
   Web of Science ®Google Scholar
• Kuo Y, Yang T, Huang GW. The use of grey relational analysis in solving multiple attribute decision-making problems. Comput Ind Eng. 2008;55:80–93.10.1016/j.cie.2007.12.002
   Web of Science ®Google Scholar
• Yang T, Wen Y, Wang F. Evaluation of robustness of supply chain information-sharing strategies using a hybrid Taguchi and multiple criteria decision-making method. Int J Prod Econ. 2011;134:458–466.10.1016/j.ijpe.2009.11.018
   Web of Science ®Google Scholar
• Pillai VM, Lavanya K, Pamulety TC. Bullwhip effect analysis using supply chain role play game and ranking of supply chains. Int J Procurement Manage. 2014;7:299–315.10.1504/IJPM.2014.060777
   Google Scholar
• Zhao X, Xie J, Leung J. The impact of forecasting model selection on the value of information sharing in a supply chain. Eur J Oper Res. 2002;142:321–344.10.1016/S0377-2217(01)00300-9
   Web of Science ®Google Scholar
• Zhao X, Xie J, Lau RSM. Improving the supply chain performance: use of forecasting models versus early order commitments. Int J Prod Res. 2001;39:3923–3939.10.1080/00207540110072236
   Web of Science ®Google Scholar
• Costantino F, Gravio GD, Shaban A, et al. Smoothing inventory decision rules in seasonal supply chains. Expert Syst Appl. 2016;44:304–319.10.1016/j.eswa.2015.08.052
   Web of Science ®Google Scholar
• Sari K. Exploring the impacts of radio frequency identification (RFID) technology on supply chain performance. Eur J Oper Res. 2010;207:174–183.10.1016/j.ejor.2010.04.003
   Web of Science ®Google Scholar
• Chiang WK, Feng Y. The value of information sharing in the presence of supply uncertainty and demand volatility. Int J Prod Res. 2007;45:1429–1447.10.1080/00207540600634949
   Web of Science ®Google Scholar
• Duan Q, Liao TW. Optimization of replenishment policies for decentralized and centralized capacitated supply chains under various demands. Int J Prod Econ. 2013;142:194–204.10.1016/j.ijpe.2012.11.004
   Web of Science ®Google Scholar
• Banks J, Carson JS, Nelson BL, et al. Discrete-event system simulation. Singapore: Pearson Education Asia; 2005.
   Google Scholar