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Dynamic analysis and optimization of a production control system under supply and demand uncertainties. (English) Zbl 1374.90148
Summary: This study investigates the dynamic performance and optimization of a typical discrete production control system under supply disruption and demand uncertainty. Two different types of uncertain demands, disrupted demand with a step change in demand and random demand, are considered. We find that, under demand disruption, the system’s dynamic performance indicators (the peak values of the order rate, production completion rate, and inventory) increase with the duration of supply disruption; however, they increase and decrease sequentially with the supply disruption start time. This change tendency differs from the finding that each kind of peak is independent of the supply disruption start time under no demand disruption. We also find that, under random demand, the dynamic performance indicators (Bullwhip and variance amplification of inventory relative to demand) increase with the disruption duration, but they have a decreasing tendency as demand variance increases. In order to design an adaptive system, we propose a genetic algorithm that minimizes the respective objective function on the system’s dynamic performance indicators via choosing appropriate system parameters. It is shown that the optimal parameter choices relate closely to the supply disruption start time and duration under disrupted demand and to the supply disruption duration under random demand.
MSC:
90B30 Production models
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[1] Matsuo, H., Implications of the Tohoku earthquake for Toyota’s coordination mechanism: supply chain disruption of automotive semiconductors, International Journal of Production Economics, 161, 217-227, (2015)
[2] Norrman, A.; Jansson, U., Ericsson’s proactive supply chain risk management approach after a serious sub-supplier accident, International Journal of Physical Distribution & Logistics Management, 34, 5, 434-456, (2004)
[3] Yoshiko, H., Industry picks up after Kobe earthquake, Electronic Engineering Times, 832, 4, (1995)
[4] Hendricks, K. B.; Singhal, V. R., The effect of supply chain glitches on shareholder wealth, Journal of Operations Management, 21, 5, 501-522, (2003)
[5] Chen, K.; Xiao, T., Demand disruption and coordination of the supply chain with a dominant retailer, European Journal of Operational Research, 197, 1, 225-234, (2009) · Zbl 1157.90438
[6] Lin, C.-C.; Wang, T.-H., Build-to-order supply chain network design under supply and demand uncertainties, Transportation Research Part B: Methodological, 45, 8, 1162-1176, (2011)
[7] Chen, C.-W.; Fan, Y., Bioethanol supply chain system planning under supply and demand uncertainties, Transportation Research Part E: Logistics and Transportation Review, 48, 1, 150-164, (2012)
[8] Cho, S.-H.; Tang, C. S., Advance selling in a supply chain under uncertain supply and demand, Manufacturing & Service Operations Management, 15, 2, 305-319, (2013)
[9] Sting, F. J.; Huchzermeier, A., Dual sourcing: responsive hedging against correlated supply and demand uncertainty, Naval Research Logistics, 59, 1, 69-89, (2012) · Zbl 1407.90039
[10] John, S.; Naim, M. M.; Towill, D. R., Dynamic analysis of a WIP compensated decision support system, International Journal of Manufacturing System Design, 1, 4, 283-297, (1994)
[11] Mason-Jones, R.; Naim, M. M.; Towill, D. R., The impact of pipeline control on supply chain dynamics, The International Journal of Logistics Management, 8, 2, 47-62, (1997)
[12] Disney, S.; Naim, M.; Towill, D., Dynamic simulation modelling for lean logistics, International Journal of Physical Distribution &Logistics Management, 27, 3-4, 174-196, (1997)
[13] Dejonckheere, J.; Disney, S. M.; Lambrecht, M. R.; Towill, D. R., Measuring and avoiding the bullwhip effect: a control theoretic approach, European Journal of Operational Research, 147, 3, 567-590, (2003) · Zbl 1026.90030
[14] Disney, S. M.; Towill, D. R., The effect of vendor managed inventory (VMI) dynamics on the Bullwhip Effect in supply chains, International Journal of Production Economics, 85, 2, 199-215, (2003)
[15] Zhou, L.; Disney, S.; Towill, D. R., A pragmatic approach to the design of bullwhip controllers, International Journal of Production Economics, 128, 2, 556-568, (2010)
[16] Wang, X.; Disney, S. M.; Wang, J., Exploring the oscillatory dynamics of a forbidden returns inventory system, International Journal of Production Economics, 147, 3-12, (2014)
[17] Forrester, J. W., Industrial dynamics: a major breakthrough for decision makers, Harvard Business Review, 36, 4, 37-66, (1958)
[18] Towill, D. R., Dynamic analysis of an inventory and order based productioncontrol system, The International Journal of Production Research, 20, 6, 671-687, (1982)
[19] Disney, S. M.; Potter, A. T.; Gardner, B. M., The impact of vendor managed inventory on transport operations, Transportation Research Part E: Logistics and Transportation Review, 39, 5, 363-380, (2003)
[20] Zhou, L.; Naim, M. M.; Tang, O.; Towill, D. R., Dynamic performance of a hybrid inventory system with a Kanban policy in remanufacturing process, Omega, 34, 6, 585-598, (2006)
[21] Oke, A.; Gopalakrishnan, M., Managing disruptions in supply chains: a case study of a retail supply chain, International Journal of Production Economics, 118, 1, 168-174, (2009)
[22] Li, J.; Wang, S.; Cheng, T. C. E., Competition and cooperation in a single-retailer two-supplier supply chain with supply disruption, International Journal of Production Economics, 124, 1, 137-150, (2010)
[23] Sheffi, Y.; Rice, J. B., A supply chain view of the resilient enterprise, MIT Sloan Management Review, 47, 1, 41-94, (2005)
[24] Kleindorfer, P. R.; Saad, G. H., Managing disruption risks in supply chains, Production and Operations Management, 14, 1, 53-68, (2005)
[25] Schmitt, A. J.; Snyder, L. V.; Shen, Z. J. M., Inventory systems with stochastic demand and supply: properties and approximations, European Journal of Operational Research, 206, 2, 313-328, (2010) · Zbl 1188.90017
[26] Ellis, S. C.; Henry, R. M.; Shockley, J., Buyer perceptions of supply disruption risk: a behavioral view and empirical assessment, Journal of Operations Management, 28, 1, 34-46, (2010)
[27] Yu, H.; Zeng, A. Z.; Zhao, L., Single or dual sourcing: decision-making in the presence of supply chain disruption risks, Omega, 37, 4, 788-800, (2009)
[28] Wang, Y.; Gilland, W.; Tomlin, B., Mitigating supply risk: dual sourcing or process improvement?, Manufacturing & Service Operations Management, 12, 3, 489-510, (2010)
[29] Xanthopoulos, A.; Vlachos, D.; Iakovou, E., Optimal newsvendor policies for dual-sourcing supply chains: a disruption risk management framework, Computers and Operations Research, 39, 2, 350-357, (2012) · Zbl 1251.90042
[30] Kouvelis, P.; Milner, J. M., Supply chain capacity and outsourcing decisions: the dynamic interplay of demand and supply uncertainty, IIE Transactions, 34, 8, 717-728, (2002)
[31] Babich, V., Vulnerable options in supply chains: effects of supplier competition, Naval Research Logistics, 53, 7, 656-673, (2006) · Zbl 1106.90007
[32] Tomlin, B.; Wang, Y., On the value of mix flexibility and dual sourcing in unreliable newsvendor networks, Manufacturing & Service Operations Management, 7, 1, 37-57, (2005)
[33] Xiao, T.; Yu, G.; Sheng, Z.; Xia, Y., Coordination of a supply chain with one-manufacturer and two-retailers under demand promotion and disruption management decisions, Annals of Operations Research, 135, 1, 87-109, (2005) · Zbl 1112.90305
[34] Xiao, T.; Qi, X., Price competition, cost and demand disruptions and coordination of a supply chain with one manufacturer and two competing retailers, Omega, 36, 5, 741-753, (2008)
[35] Soleimani, F.; Arshadi Khamseh, A.; Naderi, B., Optimal decisions in a dual-channel supply chain under simultaneous demand and production cost disruptions, Annals of Operations Research, 243, 1-2, 301-321, (2016) · Zbl 1348.90041
[36] Wang, Y.; Gerchak, Y., Periodic review production models with variable capacity, random yield, and uncertain demand, Management Science, 42, 1, 130-137, (1996) · Zbl 0851.90059
[37] Kazaz, B., Production planning under yield and demand uncertainty with yield-dependent cost and price, Manufacturing and Service Operations Management, 6, 3, 209-224, (2004)
[38] Li, Q.; Xu, H.; Zheng, S., Periodic-review inventory systems with random yield and demand: bounds and heuristics, IIE Transactions, 40, 4, 434-444, (2008)
[39] Feng, Q., Integrating dynamic pricing and replenishment decisions under supply capacity uncertainty, Management Science, 56, 12, 2154-2172, (2010) · Zbl 1232.90045
[40] Kouvelis, P.; Li, J., Offshore outsourcing, yield uncertainty, and contingency responses, Production and Operations Management, 22, 1, 164-177, (2013)
[41] Peidro, D.; Mula, J.; Poler, R.; Verdegay, J.-L., Fuzzy optimization for supply chain planning under supply, demand and process uncertainties, Fuzzy Sets and Systems, 160, 18, 2640-2657, (2009) · Zbl 1279.90206
[42] Yang, R.; Ma, L., Two-part tariff contracting with competing unreliable suppliers in a supply chain under asymmetric information, Annals of Operations Research, 2015, 1, 1-31, (2015) · Zbl 1401.90042
[43] Petrovic, D.; Roy, R.; Petrovic, R., Modelling and simulation of a supply chain in an uncertain environment, European Journal of Operational Research, 109, 2, 299-309, (1998) · Zbl 0937.90047
[44] Schmitt, A. J.; Singh, M., Quantifying supply chain disruption risk using Monte Carlo and discrete-event simulation, Proceedings of the Winter Simulation Conference (WSC ’09)
[45] Schmitt, A. J.; Singh, M., A quantitative analysis of disruption risk in a multi-echelon supply chain, International Journal of Production Economics, 139, 1, 22-32, (2012)
[46] Jung, J. Y.; Blau, G.; Pekny, J. F.; Reklaitis, G. V.; Eversdyk, D., Integrated safety stock management for multi-stage supply chains under production capacity constraints, Computers and Chemical Engineering, 32, 11, 2570-2581, (2008)
[47] Mahnam, M.; Yadollahpour, M. R.; Famil-Dardashti, V.; Hejazi, S. R., Supply chain modeling in uncertain environment with bi-objective approach, Computers and Industrial Engineering, 56, 4, 1535-1544, (2009)
[48] Mohebbi, E.; Choobineh, F., The impact of component commonality in an assemble-to-order environment under supply and demand uncertainty, Omega, 33, 6, 472-482, (2005)
[49] Wang, X.; Disney, S. M.; Wang, J., Stability analysis of constrained inventory systems with transportation delay, European Journal of Operational Research, 223, 1, 86-95, (2012) · Zbl 1253.90035
[50] Wilson, M. C., The impact of transportation disruptions on supply chain performance, Transportation Research Part E: Logistics and Transportation Review, 43, 4, 295-320, (2007)
[51] Hosoda, T.; Disney, S. M., On the replenishment policy when the market demand information is lagged, International Journal of Production Economics, 135, 1, 458-467, (2012)
[52] Borshchev, A.; Filippov, A., From system dynamics and discrete event to practical agent based modeling: reasons, techniques, tools, Proceedings of the 22nd International Conference of the System Dynamics Society
[53] Ge, Y.; Yang, J. B.; Proudlove, N.; Spring, M., System dynamics modelling for supply-chain management: a case study on a supermarket chain in the UK, International Transactions in Operational Research, 11, 5, 495-509, (2004) · Zbl 1131.90413
[54] Riddalls, C. E.; Bennett, S., The stability of supply chains, International Journal of Production Research, 40, 2, 459-475, (2002) · Zbl 1060.91500
[55] Li, J.; Li, W. H.; Lin, Y., Port supply chain simulation model under interactive analysis, Procedia Engineering, 15, 2082-2086, (2011)
[56] Towill, D. R.; Zhou, L.; Disney, S. M., Reducing the bullwhip effect: looking through the appropriate lens, International Journal of Production Economics, 108, 1-2, 444-453, (2007)
[57] Chen, F.; Drezner, Z.; Ryan, J. K.; Simchi-Levi, D., Quantifying the bullwhip effect in a simple supply chain: the impact of forecasting, lead times, and information, Management Science, 46, 3, 436-443, (2000) · Zbl 1231.90019
[58] Sargent, R. G., Verification and validation of simulation models, Journal of Simulation, 7, 1, 12-24, (2013)
[59] Disney, S. M.; Naim, M. M.; Towill, D. R., Genetic algorithm optimisation of a class of inventory control systems, International Journal of Production Economics, 68, 3, 259-278, (2000)
[60] Darwin, C., The Origin of Species by Means of Natural Selection or, The Preservation of Favored Races in The Struggle for Life, (1859), John Murrey
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