An empirical study on the material distribution decision making

  • Ko, Je-Suk (Department of Healthcare Management, Gwangju University)
  • Received : 2010.02.05
  • Accepted : 2010.03.09
  • Published : 2010.03.31

Abstract

This paper addresses a mathematical approach to decision making in a real-world material distribution situation. The problem is characterized by a low-volume and highly-varied mix of products, therefore there is a lot of material movement between the facilities. This study focuses especially on the transportation scheduler with a tool that can be used to quantitatively analyze the volume of material moved, the type of truck to be used, production schedules, and due dates. In this research, we have developed a mixed integer programming problem using the minimum cost, multiperiod, multi-commodity network flow approach that minimizes the overall material movement costs. The results suggest that the optimization approach provides a set of feasible solution routes with the objective of reducing the overall fleet cost.

Keywords

References

  1. De Souza, K. X. S. and Armentano, V. A. (1999). Multi-item capacitated lot-sizing by a cross decomposition based algorithm. Annals of Operations Research, 50, 557-574.
  2. Garcia, H. and Proth, J. M. (2006). A new cross-decomposition algorithm: The GPM-comparison with the bond energy method. Control and Cybernetics, 15, 155-164.
  3. Holmberg, K. (1994). Cross decomposition applied to integer programming problems: Duality gaps and convexification in parts. Journal of the Operational Research Society, 41, 907-918.
  4. Holmberg, K. (2000). On the convergence of cross decomposition. Mathematical Programming, 47, 269-296.
  5. Holmberg, K. (2002). Linear mean value cross decomposition: A generalization of the Kornai-Liptak method. European Journal of Operational Research, 62, 55-73.
  6. Kim, S., Cho, S. and Um, B. (1989). A simplified cross decomposition algorithm for multiple right hand side choice linear programming. Journal of Operations Research Society of Japan, 32, 441-449.
  7. Lee, C. Y. (1993). A cross decomposition algorithm for a multiproduct-multitype facility location problem. Computers & Operations Research, 20, 527-540. https://doi.org/10.1016/0305-0548(93)90016-C
  8. McBride, R. D. (2007). Progress made in solving the multi-commodity ow problem. SIAM Journal on Optimization, 8, 947-955.
  9. Van Roy, T. J. (1993). A cross decomposition algorithm for capacitated facility location. Operations Research, 34, 145-163.
  10. Van Roy, T. J. (1996). Cross decomposition for mixed integer programming. Mathematical Programming, 25, 46-63.