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Optimizing of bullwhip effect and net stock amplification in three-echelon supply chains using evolutionary multi-objective metaheuristics

Author

Listed:
  • K. Devika

    (Aalborg University)

  • A. Jafarian

    (Allame Tabataba’i University Business School (ATUBS))

  • A. Hassanzadeh

    (University of Tehran)

  • R. Khodaverdi

    (Allame Tabataba’i University Business School (ATUBS))

Abstract

In this article, we intend to model and optimize the bullwhip effect (BWE) and net stock amplification (NSA) in a three-stage supply chain consisting of a retailer, a wholesaler, and a manufacturer under both centralized and decentralized scenarios. In this regard, firstly, the causes of BWE and NSA are mathematically formulated using response surface methodology (RSM) as a multi-objective optimization model that aims to minimize the BWE and NSA on both chains. The simultaneous analysis of the BWE and NSA is considered as the main novelty of this paper. To tackle the addressed problem, we propose a novel multi-objective hybrid evolutionary approach called MOHES; MOHES is a hybrid of two known multi-objective algorithms i.e. multi-objective electro magnetism mechanism algorithm (MOEMA) and population-based multi-objective simulated annealing (PBMOSA). We applied a co-evolutionary strategy for this purpose with eligibility of both algorithms. Proposed MOHES is compared with three common and popular algorithms (i.e. NRGA, NSGAII, and MOPSO). Since the utilized algorithms are very sensitive to parameter values, RSM with the multi-objective decision making (MODM) approach is employed to tune the parameters. Finally, the hybrid algorithm and the singular approaches are compared together in terms of some performance measures. The results indicate that the hybrid approach achieves better solutions when compared with the others, and also the results show that in a decentralized chain, the order batching factor and the demand signal processing in wholesaler are the most important factors on BWE. Conversely, in a centralized chain, factors such as rationing, shortage gaming, and lead time are the most effective at reducing the BWE.

Suggested Citation

  • K. Devika & A. Jafarian & A. Hassanzadeh & R. Khodaverdi, 2016. "Optimizing of bullwhip effect and net stock amplification in three-echelon supply chains using evolutionary multi-objective metaheuristics," Annals of Operations Research, Springer, vol. 242(2), pages 457-487, July.
    • Handle: RePEc:spr:annopr:v:242:y:2016:i:2:d:10.1007_s10479-013-1517-y
    DOI: 10.1007/s10479-013-1517-y
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    1. Jaksic, Marko & Rusjan, Borut, 2008. "The effect of replenishment policies on the bullwhip effect: A transfer function approach," European Journal of Operational Research, Elsevier, vol. 184(3), pages 946-961, February.
    2. Geary, S. & Disney, S.M. & Towill, D.R., 2006. "On bullwhip in supply chains--historical review, present practice and expected future impact," International Journal of Production Economics, Elsevier, vol. 101(1), pages 2-18, May.
    3. Chandra, Charu & Grabis, Janis, 2005. "Application of multi-steps forecasting for restraining the bullwhip effect and improving inventory performance under autoregressive demand," European Journal of Operational Research, Elsevier, vol. 166(2), pages 337-350, October.
    4. Zhang, Xiaolong, 2004. "The impact of forecasting methods on the bullwhip effect," International Journal of Production Economics, Elsevier, vol. 88(1), pages 15-27, March.
    5. Manuel P. Baganha & Morris A. Cohen, 1998. "The Stabilizing Effect of Inventory in Supply Chains," Operations Research, INFORMS, vol. 46(3-supplem), pages 72-83, June.
    6. Xu, Kefeng & Dong, Yan & Evers, Philip T., 2001. "Towards better coordination of the supply chain," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 37(1), pages 35-54, March.
    7. Wright, David & Yuan, Xin, 2008. "Mitigating the bullwhip effect by ordering policies and forecasting methods," International Journal of Production Economics, Elsevier, vol. 113(2), pages 587-597, June.
    8. Chatfield, Dean C. & Pritchard, Alan M., 2013. "Returns and the bullwhip effect," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 49(1), pages 159-175.
    9. John D. Sterman, 1989. "Modeling Managerial Behavior: Misperceptions of Feedback in a Dynamic Decision Making Experiment," Management Science, INFORMS, vol. 35(3), pages 321-339, March.
    10. Varadharajan, T.K. & Rajendran, Chandrasekharan, 2005. "A multi-objective simulated-annealing algorithm for scheduling in flowshops to minimize the makespan and total flowtime of jobs," European Journal of Operational Research, Elsevier, vol. 167(3), pages 772-795, December.
    11. Naish, Howard F, 1994. "Production Smoothing in the Linear Quadratic Inventory Model," Economic Journal, Royal Economic Society, vol. 104(425), pages 864-875, July.
    12. Graves, Stephen C., 1997. "A single-item inventory model for a non-stationary demand process," Working papers WP 3944-97., Massachusetts Institute of Technology (MIT), Sloan School of Management.
    13. Li Chen & Hau L. Lee, 2009. "Information Sharing and Order Variability Control Under a Generalized Demand Model," Management Science, INFORMS, vol. 55(5), pages 781-797, May.
    14. Dobos, Imre, 2011. "The analysis of bullwhip effect in a HMMS-type supply chain," International Journal of Production Economics, Elsevier, vol. 131(1), pages 250-256, May.
    15. Luong, Huynh Trung, 2007. "Measure of bullwhip effect in supply chains with autoregressive demand process," European Journal of Operational Research, Elsevier, vol. 180(3), pages 1086-1097, August.
    16. Zhang, Xiaolong & Burke, Gerard J., 2011. "Analysis of compound bullwhip effect causes," European Journal of Operational Research, Elsevier, vol. 210(3), pages 514-526, May.
    17. Zhou, Li & Disney, Stephen & Towill, Denis R., 2010. "A pragmatic approach to the design of bullwhip controllers," International Journal of Production Economics, Elsevier, vol. 128(2), pages 556-568, December.
    18. Machuca, José A. D. & Barajas, Rafael P., 2004. "The impact of electronic data interchange on reducing bullwhip effect and supply chain inventory costs," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 40(3), pages 209-228, May.
    19. Adenso-Díaz, Belarmino & Moreno, Plácido & Gutiérrez, Ester & Lozano, Sebastián, 2012. "An analysis of the main factors affecting bullwhip in reverse supply chains," International Journal of Production Economics, Elsevier, vol. 135(2), pages 917-928.
    20. Dejonckheere, J. & Disney, S. M. & Lambrecht, M. R. & Towill, D. R., 2003. "Measuring and avoiding the bullwhip effect: A control theoretic approach," European Journal of Operational Research, Elsevier, vol. 147(3), pages 567-590, June.
    21. Ouyang, Yanfeng & Li, Xiaopeng, 2010. "The bullwhip effect in supply chain networks," European Journal of Operational Research, Elsevier, vol. 201(3), pages 799-810, March.
    22. Towill, Denis R. & Zhou, Li & Disney, Stephen M., 2007. "Reducing the bullwhip effect: Looking through the appropriate lens," International Journal of Production Economics, Elsevier, vol. 108(1-2), pages 444-453, July.
    23. Kahn, James A, 1987. "Inventories and the Volatility of Production," American Economic Review, American Economic Association, vol. 77(4), pages 667-679, September.
    24. Bayraktar, Erkan & Lenny Koh, S.C. & Gunasekaran, A. & Sari, Kazim & Tatoglu, Ekrem, 2008. "The role of forecasting on bullwhip effect for E-SCM applications," International Journal of Production Economics, Elsevier, vol. 113(1), pages 193-204, May.
    25. Ramey, Valerie A, 1991. "Nonconvex Costs and the Behavior of Inventories," Journal of Political Economy, University of Chicago Press, vol. 99(2), pages 306-334, April.
    26. Ouyang, Yanfeng & Daganzo, Carlos, 2006. "Counteracting the bullwhip effect with decentralized negotiations and advance demand information," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 363(1), pages 14-23.
    27. Stephen M. Disney & Ingrid Farasyn & Marc R. Lambrecht & Denis R. Towill & Wim Van De Velde, 2007. "Controlling bullwhip and inventory variability with the golden smoothing rule," European Journal of Industrial Engineering, Inderscience Enterprises Ltd, vol. 1(3), pages 241-265.
    28. Sucky, Eric, 2009. "The bullwhip effect in supply chains--An overestimated problem?," International Journal of Production Economics, Elsevier, vol. 118(1), pages 311-322, March.
    29. Potter, Andrew & Disney, Stephen M., 2006. "Bullwhip and batching: An exploration," International Journal of Production Economics, Elsevier, vol. 104(2), pages 408-418, December.
    30. Loukil, Taicir & Teghem, Jacques & Fortemps, Philippe, 2007. "A multi-objective production scheduling case study solved by simulated annealing," European Journal of Operational Research, Elsevier, vol. 179(3), pages 709-722, June.
    31. Ton Hien Duc, Truong & Luong, Huynh Trung & Kim, Yeong-Dae, 2010. "Effect of the third-party warehouse on bullwhip effect and inventory cost in supply chains," International Journal of Production Economics, Elsevier, vol. 124(2), pages 395-407, April.
    32. Disney, S. M. & Towill, D. R. & van de Velde, W., 2004. "Variance amplification and the golden ratio in production and inventory control," International Journal of Production Economics, Elsevier, vol. 90(3), pages 295-309, August.
    33. Hau L. Lee & V. Padmanabhan & Seungjin Whang, 1997. "Information Distortion in a Supply Chain: The Bullwhip Effect," Management Science, INFORMS, vol. 43(4), pages 546-558, April.
    34. Deshpande, Paras & Shukla, Deepak & Tiwari, M.K., 2011. "Fuzzy goal programming for inventory management: A bacterial foraging approach," European Journal of Operational Research, Elsevier, vol. 212(2), pages 325-336, July.
    35. Luong, Huynh Trung & Phien, Nguyen Huu, 2007. "Measure of bullwhip effect in supply chains: The case of high order autoregressive demand process," European Journal of Operational Research, Elsevier, vol. 183(1), pages 197-209, November.
    36. Frank Chen & Zvi Drezner & Jennifer K. Ryan & David Simchi-Levi, 2000. "Quantifying the Bullwhip Effect in a Simple Supply Chain: The Impact of Forecasting, Lead Times, and Information," Management Science, INFORMS, vol. 46(3), pages 436-443, March.
    37. Tsou, Ching-Shih, 2009. "Evolutionary Pareto optimizers for continuous review stochastic inventory systems," European Journal of Operational Research, Elsevier, vol. 195(2), pages 364-371, June.
    38. Jaksic, Marko & Rusjan, Borut, 2008. "Corrigendum to "The effect of replenishment policies on the bullwhip effect: A transfer function approach" [European Journal of Operational Research 184 (3) (2008) 946-961]," European Journal of Operational Research, Elsevier, vol. 188(1), pages 313-312, July.
    39. Sodhi, ManMohan S. & Tang, Christopher S., 2011. "The incremental bullwhip effect of operational deviations in an arborescent supply chain with requirements planning," European Journal of Operational Research, Elsevier, vol. 215(2), pages 374-382, December.
    40. Hosoda, Takamichi & Disney, Stephen M., 2006. "On variance amplification in a three-echelon supply chain with minimum mean square error forecasting," Omega, Elsevier, vol. 34(4), pages 344-358, August.
    41. Dejonckheere, J. & Disney, S. M. & Lambrecht, M. R. & Towill, D. R., 2004. "The impact of information enrichment on the Bullwhip effect in supply chains: A control engineering perspective," European Journal of Operational Research, Elsevier, vol. 153(3), pages 727-750, March.
    42. Herbert J. Vassian, 1955. "Application of Discrete Variable Servo Theory to Inventory Control," Operations Research, INFORMS, vol. 3(3), pages 272-282, August.
    43. Kelle, Peter & Milne, Alistair, 1999. "The effect of (s, S) ordering policy on the supply chain," International Journal of Production Economics, Elsevier, vol. 59(1-3), pages 113-122, March.
    44. Disney, S.M. & Farasyn, I. & Lambrecht, M. & Towill, D.R. & de Velde, W. Van, 2006. "Taming the bullwhip effect whilst watching customer service in a single supply chain echelon," European Journal of Operational Research, Elsevier, vol. 173(1), pages 151-172, August.
    45. Sterman, John D., 1989. "Misperceptions of feedback in dynamic decision making," Organizational Behavior and Human Decision Processes, Elsevier, vol. 43(3), pages 301-335, June.
    46. Rachel Croson & Karen Donohue, 2006. "Behavioral Causes of the Bullwhip Effect and the Observed Value of Inventory Information," Management Science, INFORMS, vol. 52(3), pages 323-336, March.
    47. Nepal, Bimal & Murat, Alper & Babu Chinnam, Ratna, 2012. "The bullwhip effect in capacitated supply chains with consideration for product life-cycle aspects," International Journal of Production Economics, Elsevier, vol. 136(2), pages 318-331.
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    3. Erkan Bayraktar & Kazim Sari & Ekrem Tatoglu & Selim Zaim & Dursun Delen, 2020. "Assessing the supply chain performance: a causal analysis," Annals of Operations Research, Springer, vol. 287(1), pages 37-60, April.
    4. Ponte, Borja & Dominguez, Roberto & Cannella, Salvatore & Framinan, Jose M., 2022. "The implications of batching in the bullwhip effect and customer service of closed-loop supply chains," International Journal of Production Economics, Elsevier, vol. 244(C).
    5. Sameer Prasad & Jason Woldt & Harish Borra & Nezih Altay, 2022. "Migrant supply chain networks: an empirically based typology," Annals of Operations Research, Springer, vol. 319(1), pages 1331-1358, December.
    6. Kiyoung Jeong & Jae-Dong Hong, 2019. "The impact of information sharing on bullwhip effect reduction in a supply chain," Journal of Intelligent Manufacturing, Springer, vol. 30(4), pages 1739-1751, April.
    7. Anupam Keshari & Nishikant Mishra & Nagesh Shukla & Steve McGuire & Sangeeta Khorana, 2018. "Multiple order-up-to policy for mitigating bullwhip effect in supply chain network," Annals of Operations Research, Springer, vol. 269(1), pages 361-386, October.
    8. Jafarian, Ahmad & Asgari, Nasrin & Mohri, Seyed Sina & Fatemi-Sadr, Elham & Farahani, Reza Zanjirani, 2019. "The inventory-routing problem subject to vehicle failure," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 126(C), pages 254-294.
    9. Kannan Govindan, 2016. "Evolutionary algorithms for supply chain management," Annals of Operations Research, Springer, vol. 242(2), pages 195-206, July.

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