How to cite this paper
Mahmud, S., Rahman, M., Hasan, M & Hossain, M. (2016). Minimizing the bullwhip effect in a single product multistage supply chain using genetic algorithm.Uncertain Supply Chain Management, 4(2), 137-146.
Refrences
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Cachon, G. P., & Fisher, M. (2000). Supply chain inventory management and the value of shared information. Management science, 46(8), 1032-1048.
Cachon, G. P., Randall, T., & Schmidt, G. M. (2007). In search of the bullwhip effect. Manufacturing & Service Operations Management, 9(4), 457-479.
Carlsson, C., & Fullér, R. (2001, January). Reducing the bullwhip effect by means of intelligent, soft computing methods. In System Sciences, 2001. Proceedings of the 34th Annual Hawaii International Conference on (pp. 10-pp). IEEE.
Chan, C., Cheng, C., & Huang, S. (2006). Formulating ordering policies in a supply chain by genetic algorithm. International Journal of Modelling and Simulation, 26(2), 129.
Croson, R., & Donohue, K. (2006). Behavioral causes of the bullwhip effect and the observed value of inventory information. Management Science, 52(3), 323-336.
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,153(3), 727-750.
Disney, S. M., & Towill, D. R. (2003). Vendor-management inventory and bullwhip reduction is a two-level supply chain. International Journal of Operations and Production Management, 23(6), 625-651.
Disney, S. M., Naim, M. M., & Towill, D. R. (2000). Genetic algorithm optimisation of a class of inventory control systems. International Journal of Production Economics, 68(3), 259-278.
Fransoo, J. C., & Wouters, M. J. (2000). Measuring the bullwhip effect in the supply chain. Supply Chain Management: An International Journal, 5(2), 78-89.
Forrester, J. W. (1958). Industrial dynamics: a major breakthrough for decision makers. Harvard business review, 36(4), 37-66.
Gill, P., & Abend, J. (1997). Wal-Mart: The supply chain heavyweight champ.Supply Chain Management Review, 1(1), 8-16.
Kimbrough, S. O., Wu, D. J., & Zhong, F. (2002). Computers play the beer game: can artificial agents manage supply chains?. Decision support systems,33(3), 323-333.
Kelle, P., & Milne, A. (1999). The effect of (s, S) ordering policy on the supply chain. International Journal of Production Economics, 59(1), 113-122.
Lee, H. L., Padmanabhan, V., & Whang, S. (2004). Information distortion in a supply chain: the bullwhip effect. Management science, 50(12_supplement), 1875-1886.
Lee, H. L., Padmanabhan, V., & Whang, S. (1997). The bullwhip effect in supply chains1. Sloan management review, 38(3), 93-102.
Lee, H. L., So, K. C., & Tang, C. S. (2000). The value of information sharing in a two-level supply chain. Management science, 46(5), 626-643.
Li, G., Wang, S., Yan, H., & Yu, G. (2005). Information transformation in a supply chain: a simulation study. Computers & Operations Research, 32(3), 707-725.
Merkuryeva, G., & Napalkova, L. (2008). Development of multi-objective simulation-based genetic algorithm for supply chain cyclic planning and optimisation. In Proceedings of the 20th International EURO Mini Conference" Continuous Optimisation and Knowledge-Based Technologies" (pp. 444-449).
O’Donnell, T., Humphreys, P., McIvor, R., & Maguire, L. (2009). Reducing the negative effects of sales promotions in supply chains using genetic algorithms.Expert Systems with Applications, 36(4), 7827-7837.
Potter, A., & Disney, S. M. (2006). Bullwhip and batching: An exploration.International Journal of Production Economics, 104(2), 408-418.
Riddalls, C. E., & Bennett, S. (2002). The stability of supply chains.International Journal of Production Research, 40(2), 459-475.
Sucky, E. (2009). The bullwhip effect in supply chains—An overestimated problem?. International Journal of Production Economics, 118(1), 311-322.
Wu, D. Y., & Katok, E. (2006). Learning, communication, and the bullwhip effect. Journal of Operations Management, 24(6), 839-850.
Zhou, G., Min, H., & Gen, M. (2002). The balanced allocation of customers to multiple distribution centers in the supply chain network: a genetic algorithm approach. Computers & Industrial Engineering, 43(1), 251-261.
Cachon, G. P., & Fisher, M. (2000). Supply chain inventory management and the value of shared information. Management science, 46(8), 1032-1048.
Cachon, G. P., Randall, T., & Schmidt, G. M. (2007). In search of the bullwhip effect. Manufacturing & Service Operations Management, 9(4), 457-479.
Carlsson, C., & Fullér, R. (2001, January). Reducing the bullwhip effect by means of intelligent, soft computing methods. In System Sciences, 2001. Proceedings of the 34th Annual Hawaii International Conference on (pp. 10-pp). IEEE.
Chan, C., Cheng, C., & Huang, S. (2006). Formulating ordering policies in a supply chain by genetic algorithm. International Journal of Modelling and Simulation, 26(2), 129.
Croson, R., & Donohue, K. (2006). Behavioral causes of the bullwhip effect and the observed value of inventory information. Management Science, 52(3), 323-336.
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,153(3), 727-750.
Disney, S. M., & Towill, D. R. (2003). Vendor-management inventory and bullwhip reduction is a two-level supply chain. International Journal of Operations and Production Management, 23(6), 625-651.
Disney, S. M., Naim, M. M., & Towill, D. R. (2000). Genetic algorithm optimisation of a class of inventory control systems. International Journal of Production Economics, 68(3), 259-278.
Fransoo, J. C., & Wouters, M. J. (2000). Measuring the bullwhip effect in the supply chain. Supply Chain Management: An International Journal, 5(2), 78-89.
Forrester, J. W. (1958). Industrial dynamics: a major breakthrough for decision makers. Harvard business review, 36(4), 37-66.
Gill, P., & Abend, J. (1997). Wal-Mart: The supply chain heavyweight champ.Supply Chain Management Review, 1(1), 8-16.
Kimbrough, S. O., Wu, D. J., & Zhong, F. (2002). Computers play the beer game: can artificial agents manage supply chains?. Decision support systems,33(3), 323-333.
Kelle, P., & Milne, A. (1999). The effect of (s, S) ordering policy on the supply chain. International Journal of Production Economics, 59(1), 113-122.
Lee, H. L., Padmanabhan, V., & Whang, S. (2004). Information distortion in a supply chain: the bullwhip effect. Management science, 50(12_supplement), 1875-1886.
Lee, H. L., Padmanabhan, V., & Whang, S. (1997). The bullwhip effect in supply chains1. Sloan management review, 38(3), 93-102.
Lee, H. L., So, K. C., & Tang, C. S. (2000). The value of information sharing in a two-level supply chain. Management science, 46(5), 626-643.
Li, G., Wang, S., Yan, H., & Yu, G. (2005). Information transformation in a supply chain: a simulation study. Computers & Operations Research, 32(3), 707-725.
Merkuryeva, G., & Napalkova, L. (2008). Development of multi-objective simulation-based genetic algorithm for supply chain cyclic planning and optimisation. In Proceedings of the 20th International EURO Mini Conference" Continuous Optimisation and Knowledge-Based Technologies" (pp. 444-449).
O’Donnell, T., Humphreys, P., McIvor, R., & Maguire, L. (2009). Reducing the negative effects of sales promotions in supply chains using genetic algorithms.Expert Systems with Applications, 36(4), 7827-7837.
Potter, A., & Disney, S. M. (2006). Bullwhip and batching: An exploration.International Journal of Production Economics, 104(2), 408-418.
Riddalls, C. E., & Bennett, S. (2002). The stability of supply chains.International Journal of Production Research, 40(2), 459-475.
Sucky, E. (2009). The bullwhip effect in supply chains—An overestimated problem?. International Journal of Production Economics, 118(1), 311-322.
Wu, D. Y., & Katok, E. (2006). Learning, communication, and the bullwhip effect. Journal of Operations Management, 24(6), 839-850.
Zhou, G., Min, H., & Gen, M. (2002). The balanced allocation of customers to multiple distribution centers in the supply chain network: a genetic algorithm approach. Computers & Industrial Engineering, 43(1), 251-261.