Abstract
Maintaining an effective management of supply chain even in the disasters is becoming crucial issue for manufacturing industry, because the contemporary supply chain networks become global and complex and the behaviors of the network are hardly predictable. The Beer Game is a simple but very useful example of supply chain management. The game consists of four sectors: factory, distributor, wholesaler, and retailer and deliver the beer to the customers. Many business schools adopt it to learn the key point of supply chain. In this study, computer agents play the game instead of humans. Agents are evolved with a genetic algorithm. We examine how the agents handle the game especially when some part of supply chain exhibit malfunction. Through simulations, we confirmed that effective ordering strategies are different between sectors.
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References
Hugos, M.H.: Essentials of Supply Chain Management third edition, Wiley (2011)
MacKenzie, C.A., Santos, J.R., Barker, K.: Measuring changes in international production from a disruption: Case study of the Japanese earthquake and tsunami. International Journal of Production Economics 138(2), 293–302 (2012)
Sterman, J.D.: Flight Simulator for Management Education, http://web.mit.edu/jsterman/www/SDG/beergame.html
Jarmain, W.E.: Problems in Industrial Dynamics. MIT Press, Cambridge (1963)
Sterman, J.D.: Modeling managerial behaviour: mis-perceptions of feedback in a dynamic decision making experiment Management Science 35, 321–339 (1989)
Strozzi, F., Bosch, J., Zaldivar, J.: M., Beer game order policy optimization under changing customer demand. Decision Support Systems 42(4), 2153–2163 (2007)
O’Donnell, T., Maguire, L., McIvor, R., Humphreys, P.: Minimizing the bullwhip effect in a supply chain using genetic algorithms. International Journal of Production Research 44(8), 1523–1543 (2006)
Steven, O., Kimbrough, D.J.: Wu, Fang Zhong, Computers Play the Beer Game: Can Artificial Agents Man-age Supply Chains? Decision Support Systems 33(3), 323–333 (2002)
Akimoto, Y., Hasada, R., Sakuma, J., Ono, I., Kobayashi, S.: Generation Alternation Model for Real-coded GA Using Multi-Parent Proposal and Evaluation of Just Generation Gap (JGG). In: SICE Symposium on Decentralized Autonomous Systems, vol. 19, pp. 341–346 (2007) (in Japanese)
Kobayashi, S.: The Frontiers of Real-Coded Genetic Algorithms, Transactions of Japanese Society for Artificial Intelligence 24(1), 147–162 (2009) (in Japanese)
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Sato, H., Shirakawa, T., Kubo, M., Namatame, A. (2015). The Impact of the Malfunction of a Sector in Supply Chain on the Ordering Policy of Each Sector. In: Handa, H., Ishibuchi, H., Ong, YS., Tan, KC. (eds) Proceedings of the 18th Asia Pacific Symposium on Intelligent and Evolutionary Systems - Volume 2. Proceedings in Adaptation, Learning and Optimization, vol 2. Springer, Cham. https://doi.org/10.1007/978-3-319-13356-0_49
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DOI: https://doi.org/10.1007/978-3-319-13356-0_49
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-13355-3
Online ISBN: 978-3-319-13356-0
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