Abstract
In Chap. 7, stochastic programming model is employed to formulate a lateral transshipment problem, and different solution methods were examined for their efficiency in providing solutions and in combining policies enforcing preventive or emergency lateral transshipments. The importance of improving the efficiency of the whole production and distribution system is increasing while the competition among companies is becoming severe in the recent economic environment. Companies need to review the entire supply chain for productivity improvement, the importance of tools to support optimal supply chain design is increasing. Numerous studies of mathematical programming for supply chain design problems have been made. Research that attempts to construct an efficient solution to the problem is mainstream. When applying supply chain design problems to real problems, these problems become often a large-scale problems where the number of data is huge. It is extremely difficult to solve the problem and calculate a good solution. In order to properly implement the supply chain design, collecting related data also takes enormous time and cost. Constructing an efficient solution is important in order to make effective use of the collected data to achieve cost reduction. In recent supply chains, suppliers aim to improve service levels while satisfying the diverse needs of consumers. At the same time we are considering reducing inventory and related expenses. However, in order to improve the service level, many inventories are required. There is a trade-off between inventory retention and service level. In order to improve both at the same time, it is necessary to construct a supply chain from the planning stage. Therefore, it may cost a lot of investment cost. Meanwhile, as a method of improving both inventory and service at the operation level, inventory distribution among sites has been drawing attention, and it is beginning to be utilized at actual companies’ sites. Conventional research on inventory distribution involves preventive transshipment and emergency transshipment, however two inventory transfer strategies are studied separately. Each of them has merits and demerits, and it is considered that higher service levels can be achieved by using these two policies in combination. In this chapter, considering combining these policies, and the effectiveness of the model is verified.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Agrawal, V., Chao, X., & Seshadri, S. (2004). Dynamic balancing of inventory in supply chains. European Journal of Operational Research, 159, 296–317.
Allen, S. G. (1958). Redistribution of total stock over several user locations. Redistribution of Total Stock Over Several User Locations, 5, 51–59.
Banerjee, A., Burton, J., & Banerjee, S. (2003). A simulation study of lateral transshipments in a single supplier multiple buyers supply chain network. International Journal of Production Economics, 81–82, 103–114.
Herer, Y., Tzur, M., & Yucesan, E. (2002). Transshipments: An emerging inventory recourse to achieve supply chain leagility. International Journal of Production Economics, 80, 201–212.
Herer, Y., Tzur, M., & Yucesan, E. (2006). The multi-location transshipment problem. IIE Transactions, 38, 185–200.
Karmarkar, U. S., & Patel, N. (1977). The one-period n-location distribution problem. Naval Research Logistics Quarterly, 24, 559–575.
Krishnan, K., & Rao, V. (1965). Inventory control in n warehouses. Journal of Industrial Engineering, XVI, 212–215.
Paterson, C., Kiesmüller, G., Teunter, R., & Glazebrook, K. (2011). Inventory models with lateral transshipments: A review. European Journal of Operational Research, 210, 125–136.
Robinson, L. W. (1990). Optimal an approximate policies in multiperiod, multilocation inventory models with transshipments. Operations Research, 38, 278–295.
Tagaras, G. (1999). Pooling in multi-location periodic inventory distribution systems. Omega, 27, 39–59.
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Nature Singapore Pte Ltd.
About this chapter
Cite this chapter
Xu, C., Shiina, T. (2018). Inventory Distribution Problem. In: Risk Management in Finance and Logistics. Translational Systems Sciences, vol 14. Springer, Singapore. https://doi.org/10.1007/978-981-13-0317-3_7
Download citation
DOI: https://doi.org/10.1007/978-981-13-0317-3_7
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-13-0316-6
Online ISBN: 978-981-13-0317-3
eBook Packages: Economics and FinanceEconomics and Finance (R0)