An Application of Signed-Distance Ranking Function Methodology to the Multi-Item Inventory Optimization Model within a Supply Chain

Authors

S. S. Appadoo Associate Professor Author
Heather H. Kim Assistant Professor Author

Keywords:

Randomness, Arbitrariness, Uncertainty, Multi-item economic order model (MI-EOQ), Fuzzy Distribution, Ranking Function

Abstract

In this paper, we revisit the multi-item economic order quantity inventory model (MI-EOQ) under uncertainty, arbitrariness and randomness. To solve such a problem, we use the signed distance ranking function methodology. In our approach, we quantify the model parameters in the MI-EOQ inventory model by fuzzy distribution function rather than random variables. Numerical examples are provided towards the end of the paper to illustrate the salient point in the model formulation. The proposed methodology to the MIEOQ inventory model can be easily extended to other more complex inventory models whose models parameters cannot be obtained precisely.

Author Biographies

S. S. Appadoo, Associate Professor

Department of Supply Chain Management
University of Manitoba, Winnipeg, Manitoba, Canada
November 30, 2013
Heather H. Kim, Assistant Professor

Department of Supply Chain Management
University of Manitoba, Winnipeg, Manitoba, Canada

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Published

2014-01-30

Issue

Vol. 2 No. 8 (2014): JANUARY 2014

Section

Articles

License

Copyright (c) 2014 Academic Research Publishers

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

An Application of Signed-Distance Ranking Function Methodology to the Multi-Item Inventory Optimization Model within a Supply Chain. (2014). International Academic Research Journal of Business and Management, 2(8), 29-38. https://www.acrpub.com/index.php/iarjbm/article/view/125

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