A regression-based improvement to the multiple criteria ABC inventory classification analysis

The aim of this paper is to propose a regression-based approach for obtaining a set of weights for multi-criteria ABC inventory analysis, which differ across classification criteria but are common across inventory items and follow a predetermined descending ordering scheme regarding the relative imp...

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Veröffentlicht in:Annals of operations research Jg. 306; H. 1-2; S. 369 - 382
Hauptverfasser: Karagiannis, Giannis, Paleologou, Suzanna M.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York Springer US 01.11.2021
Springer
Springer Nature B.V
Schlagworte:
Analysis
Business and Management
Classification
Combinatorics
Greece
Industrial research
Inventory control
Linear programming
Management science
Methods
Multiple criterion
Nonlinear programming
Operations research
Operations Research/Decision Theory
Regression analysis
S.I.: Regression Methods based on OR techniques
Theory of Computation
Greece
ABC inventory
Multi-criteria analysis
Regression methods
ISSN:0254-5330, 1572-9338
Online-Zugang:Volltext
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Zusammenfassung:The aim of this paper is to propose a regression-based approach for obtaining a set of weights for multi-criteria ABC inventory analysis, which differ across classification criteria but are common across inventory items and follow a predetermined descending ordering scheme regarding the relative importance of classification criteria. The proposed alternative is based on the Inequality Constrained Least Squared model and is to be compared with the existing linear and non-linear programming models available in the literature.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:0254-5330
1572-9338
DOI:10.1007/s10479-020-03788-1