A Weighted Least-Square Dissimilarity Approach for Multiple Criteria ABC Inventory Classification

Sisi Wu, Yelin Fu, K. K. Lai () and W. K. John Leung ()
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Sisi Wu: School of Management, University of Science and Technology of China, Hefei, P. R. China2Department of Information Systems, City University of Hong Kong, Hong Kong
Yelin Fu: College of Economics, Shenzhen University, Shenzhen, P. R. China4Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Hong Kong
K. K. Lai: College of Economics, Shenzhen University, Shenzhen, P. R. China
W. K. John Leung: Department of Marketing, City University of Hong Kong, Hong Kong

Asia-Pacific Journal of Operational Research (APJOR), 2018, vol. 35, issue 04, 1-12

Abstract: The present paper develops a weighted least-square dissimilarity approach to address the Multiple Criteria ABC inventory classification problem, when the different criteria ranking makes impossible to achieve a group consensus. The proposed approach effectively eliminates drawbacks regarding subjective judgements of multiple decision makers on the criteria importance, and comprehensively aggregates all rankings of the criteria importance to provide a more reasonable and effective classification mechanism. The common weights associated with all rankings are determined. An illustrative example is presented to compare the performance of our approach with the existing studies.

Keywords: Inventory ABC analysis; aggregation; weights (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (1)

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DOI: 10.1142/S0217595918500252

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