Browse > Article

Optimal Allocation of Purchase Orders in Dynamic Bidding  

Rim, Suk-Chul (Division of Industrial & Information Systems Engineering, Ajou University)
Lee, Sang-Won (Division of Industrial & Information Systems Engineering, Ajou University)
Kim, Hyun-Soo (Major of Industrial Engineering, Kyonggi University)
Publication Information
Journal of Korean Institute of Industrial Engineers / v.33, no.3, 2007 , pp. 322-328 More about this Journal
Abstract
Highly standardized products are suitable for automated purchasing using electronic commerce technology, where the price becomes the most important factor. Suppliers can change the prices dynamically based on the inventory level and market situation in order to maximize the sales and profit. In the virtual marketplace where multiple customers purchase multiple standardized products from multiple suppliers repetitively, customers can purchase the required amount of each item as a dynamic bidding by allocating purchase orders to the suppliers based on the current price. Customers need a method to quickly determine the optimal allocation of orders to the suppliers using the dynamically changing data to minimize the total cost. We present a LP model which minimizes the sum of the total price plus transportation cost for this problem. Simulation results using random data show meaningful reduction of the total cost.
Keywords
Purchase Order Allocation; Dynamic Bidding; Multiple Sourcing;
Citations & Related Records
연도 인용수 순위
  • Reference
1 Kawtummachai, R. and Van Hop, N. (2005), Order allocation in a multiple-supplier environment. International Journal of Production economics, 93-94, 231-238
2 Moore, D. L. and Fearson, H. E. (1973), Computer-assisted decision-making in purchasing. Journal of Purchasing, 9(4), 5-25
3 Pan, A. C. (1989), Allocation of order quantity among suppliers. Journal of Purchasing and Materials Management, 25(3),36-39   DOI
4 Ghodsypour, S. H. and O'Brien, C. (1998), A decision support system for supplier selection using an integrated analytic hierarchy process and linear programming. International Journal of Production Economics, 56-57, 199-212
5 Ghodsypour, S. H. and O'Brien, C. (2001), The total cost of logistics in supplier selection, under conditions of multiple sourcing, multiple criteria and capacity constraint. International journal of production economics, 73, 15-27   DOI   ScienceOn
6 Jeong, C. S. and Lee, Y. H. (2001), A Multiple-Criteria Supplier Selection (MCSS) Model for Supply Chain Management. Proceedings of the 2000 Conference on Korean Institute of Industrial Engineers. Seoul
7 Joel, D. Wisner, G., Keong Leong, Keah-Choon Tan. (2005), Principle of Supply Chain Management : A Balanced Approach, Thomson South-Western
8 Kim, S. H. and Kim, J. H. (2003), An empirical study on relative importance of supplier selection criteria - an application if the AHP in Korean Electronic Industry. Journal of Korea Productivity. 14(10), 3-25
9 U.S. Census Bureau. (2002), Annual Survey of Manufacurers, Statistics for Industry Groups and Industries, 2000
10 Jeong, H. K., Kim, J. G. and Jang, G. S. (2000), Strategic Selection of Supplier and Allocation of Order Quantities of Parts for Supply Chain Management in Automotive Parts Manufacturer. Proceedings of the 2000 Conference on Korean Institute of Industrial Engineers. Seoul
11 Park, D. and Krishnan, H. A. (2001), Understanding supplier selection practice: Differences between U.S. and Korean Executives. Thunderbird International business Review, 28, 225-243
12 Seshadri, S., Chatterjee, K., and Lilien G. L. (1991), Multiple source procurement competitions. Marketing Science, 10(3), 246-253   DOI   ScienceOn
13 Anthony, T. F. and Buffa, F. P. (1977), Strategic Purchasing scheduling. Journal of Purchasing and Materials Management, 13(3), 27-31   DOI
14 Christopher, M. (1998), Logistics and Supply Chain Management: Strategies for Reducing Cost and Improving Service, 2nd Edition, Prentice Hall