Supplier Selection and Order Allocation Based on Integer Programming

Hayden Beauchamp, Clara Novoa and Farhad Ameri
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Hayden Beauchamp: Energy Solutions, Richland, WA, USA
Clara Novoa: Ingram School of Engineering, Texas State University, San Marcos, TX, USA
Farhad Ameri: Department of Engineering Technology, Texas State University, San Marcos, TX, USA

International Journal of Operations Research and Information Systems (IJORIS), 2015, vol. 6, issue 3, 60-79

Abstract: The ability to assess and select new suppliers quickly and efficiently is a critical requirement for improving the agility of manufacturing supply chains. The Digital Manufacturing Market (DMM) is a web-based platform for intelligent supply chain configuration. This research enhances the DMM's performance by developing a column generation method for solving the supplier selection problem. The objective of the proposed method is to maximize the technological competencies of the selected suppliers while meeting their capacity constraints. The column generation method resolves the issue of limited scalability of a traditional linear programming formulation and can be integrated into the DMM. Additionally, using test generated problems, this research evaluates the effect on reducing the threshold distance traveled by semi-finished parts in the work orders. The results show that an economy of distance can be imposed with little effect on average match compatibility.

Date: 2015
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