A UNIFIED DECISION FRAMEWORK FOR INVENTORY CLASSIFICATION THROUGH GRAPH THEORY

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Published Sep 13, 2017
Bivash Mallick Bijan Sarkar Santanu Das

Abstract

Conventionally, a traditional ABC analysis based on a single criterion of annual consumption cost is employed in industry to facilitate classification of inventory items. However, other criteria may be important in inventory classification such as lead time, item criticality, storage cost, etc. Hence, for situations like this many multiple criteria decision-making methods are available and the Analytic Hierarchy Process (AHP) is a popular one. The present article demonstrates a new approach by integrating Graph Theory (GT) and the Analytic Hierarchy Process (AHP) as a decision analysis tool for multi-criteria inventory classification. In this paper, 47 disposable items used in a respiratory therapy unit of a hospital were considered for a case study. Output of this hybrid method shows more precise results than that of either traditional ABC or the AHP classification methods. As the proposed decision analysis tool is a simple, logical, systematic and consistent method, it may be recommended for application in diverse industries handling multi-criteria inventory classification systems.

https://doi.org/10.13033/ijahp.v9i2.482

How to Cite

Mallick, B., Sarkar, B., & Das, S. (2017). A UNIFIED DECISION FRAMEWORK FOR INVENTORY CLASSIFICATION THROUGH GRAPH THEORY. International Journal of the Analytic Hierarchy Process, 9(2). https://doi.org/10.13033/ijahp.v9i2.482

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Keywords

ABC classification, graph theory, analytic hierarchy process, inventory classification, graph theory-AHP integration, hybrid system

References
Bhattacharya, A., Sarkar, B., & Mukherjee, S. K. (2007). Distance-based consensus method for ABC analysis. International Journal of Production Research, 45(15), 3405–3420. Doi: https://doi.org/10.1080/00207540600847145

Braglia, M., Grassi, A., & Montanari, R. (2004). Multi-attribute classification method for spare parts inventory management. Journal of Quality in Maintenance Engineering, 10(1), 55–65. Doi: https://doi.org/10.1108/13552510410526875

Cakir, O., & Canbolat, M. S. (2008). A web-based decision support system for multi-criteria inventory classification using fuzzy AHP methodology. Expert Systems with Applications, 35(3), 1367–1378. Doi: https://doi.org/10.1016/j.eswa.2007.08.041

Chakladar, N. Das, Das, R., & Chakraborty, S. (2009). A digraph-based expert system for non-traditional machining processes selection. International Journal of Advanced Manufacturing Technology, 43(3–4), 226–237. Doi: https://doi.org/10.1007/s00170-008-1713-0

Cohen, M. A., & Ernst, R. (1988). Multi-item classification and generic inventory stock control policies. Production and Inventory Management Journal, 29(3), 6–8. Doi: https://doi.org/10.1017/CBO9781107415324.004

Darvish, M., Yasaei, M., & Saeedi, A. (2009). Application of the graph theory and matrix methods to contractor ranking. International Journal of Project Management, 27(6), 610–619. Doi: https://doi.org/10.1016/j.ijproman.2008.10.004

Faisal, M. N., Banwet, D. K., & Shankar, R. (2007). Quantification of risk mitigation environment of supply chains using graph theory and matrix methods. European Journal of Industrial Engineering, 1(1), 22–39. Doi: https://doi.org/10.1504/EJIE.2007.012652

Flores, B. E., Olson, D. L., & Dorai, V. K. (1992). Management of multicriteria inventory classification. Mathematical and Computer Modelling, 16(12), 71–82. Doi: https://doi.org/10.1016/0895-7177 (92)90021-C

Flores, B. E., & Whybark, D. C. (1986). Multiple criteria ABC analysis. International Journal of Operations & Production Management, 6(3), 38–46. Doi: http://dx.doi.org/10.1108/eb054765

Flores, B. E., & Whybark, D. C. (1987). Implementing Multiple criteria ABC analysis. Journal of Operations Management, 7(1–2), 79–85. https://doi.org/10.1016/0272-6963(87)90008-8. Doi: 10.1016/0272-6963(87)90008-8

Ghorabaee, M. K. (2015). Multi-Criteria Inventory Classification using a new method of Evaluation Based on Distance from Average Solution (EDAS). Informatica (Netherlands), 26(3), 435–451. Doi: https://doi.org/10.15388/Informatica.2015.57

Grover, S., Agrawal, V. P., & Khan, I. (2004). A digraph approach to TQM evaluation of an industry. International Journal of Production Research, 42(19), 4031–4053. Doi: https://doi.org/10.1080/00207540410001704032

Guvenir, H., & Erel, E. (1998). Multicriteria inventory classification using a genetic algorithm. European Journal of Operational Research, 105(1), 29–37. Doi: https://doi.org/10.1016/S0377-2217(97)00039-8

Kabir, G., & Hasin, M.A.A. (2013). Multi-criteria inventory classification through integration of fuzzy analytic hierarchy process and artificial neural network. International Journal and Systems Engineering, 14(1), 74–103. Doi: https://doi.org/10.1504/IJISE.2013.052922

Lanjewar P. B., Rao R. V., Kale A. V., Taler J. and Ocłoń P(2016). Evaluation and selection of energy technologies using an integrated graph theory and analytic hierarchy process methods. Decision Science Letters, 5, 327–348

Liu, J., Liao, X., Zhao, W., & Yang, N. (2016). A classification approach based on the outranking model for multiple criteria ABC analysis. Omega, 61, 19–34. Doi: https://doi.org/10.1016/j.omega.2015.07.004

Mallick, B., Dutta, O. N., & Das, S. (2012). A case study on inventory management using selective control techniques. Journal of The Association of Engineers, India, 82(1&2), 10–24. Doi:10.22485/jaei/2012/v82/i1-2/119950

Mallick, B., Sarkar, B., & Das, S. (2016). Application of the MOORA Method for Multi-Criteria Inventory Classification. In Proceeding of the International Conference on Frontiers in Optimization: Theory and Applications, Kolkata (p. 40).

Millet, I. & Schoner, B., (2005). Incorporating negative values into the Analytic Hierarchy Process, Computers & Operations Research, 32(12), 3163–3173.

Paramasivam, V., Senthil, V., & Rajam Ramasamy, N. (2011). Decision making in equipment selection: An integrated approach with digraph and matrix approach, AHP and ANP. International Journal of Advanced Manufacturing Technology, 54(9–12), 1233–1244. Doi: https://doi.org/10.1007/s00170-010-2997-4

Rao R. V. (2007). Decision making in the manufacturing environment: using graph theory and fuzzy multiple attribute decision making methods. (pp. 7–25). Springer Science & Business Media. Doi: 10.1007/978-1-4471-4375-8

Ramanathan, R. (2006). ABC inventory classification with multiple-criteria using weighted linear optimization. Computers and Operations Research, 33(3), 695–700. Doi: https://doi.org/10.1016/j.cor.2004.07.014

Rao, R. V., & Parnichkun, M. (2009). Flexible manufacturing system selection using a combinatorial mathematics-based decision-making method. International Journal of Production Research, 47(24),6981-6998.

Reid, R. A. (1987). The ABC method in hospital inventory management: a practical approach. Production and Inventory Management Journal, 28(4), 67–70.

Saaty, T. L. (1980). The Analytic Hierarchy Process. McGraw-Hill Inc. Doi: https://doi.org/0070543712

Singh, D., & Rao, R. (2011). A hybrid multiple attribute decision making method for solving problems of industrial environment. International Journal of Industrial Engineering Computations, 2(3), 631-644.

Soylu, B., & Akyol, B. (2014). Multi-criteria inventory classification with reference items.Computers & Industrial Engineering, 69, 12–20. Doi: https://doi.org/10.1016/j.cie.2013.12.011

Torabi, S. A., Hatefi, S. M., & Pay, B. S. (2012). ABC inventory classification in the presence of both quantitative and qualitative criteria. Computers and Industrial Engineering, 63(2), 530–537. Doi: https://doi.org/10.1016/j.cie.2012.04.011

Wagner, S. M., & Neshat, N. (2010). Assessing the vulnerability of supply chains using graph theory. International Journal of Production Economics, 126(1), 121–129. Doi: https://doi.org/10.1016/j.ijpe.2009.10.007

Zhou, P., & Fan, L. (2007). Short Communication A note on multi-criteria ABC inventory classification using weighted linear optimization. European Journal of Operational Research, 182(3), 1488–1491. Doi: https://doi.org/10.1016/j.ejor.2006.08.052
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