Journal ArticleDOI
ABC classification according to Pareto’s principle: a hybrid methodology
TLDR
A number of hybrid methodologies including Shannon’s entropy, TOPSIS (the technique for order preference by similarity to ideal solution) and goal programming are respectively used for determining the weight of criteria which are effective in the inventory items classification, calculations of each item value and its classification based on Pareto's principle.Abstract:
So far, many methods have been proposed to classify items based on ABC analysis, but the results of these methods have had relatively low compliance with the principles of ABC. More precisely, collective value and sometimes the number of items belonging to each category in the methods provided do not meet the basic requirements of ABC called Pareto’s principle. In this study, a number of hybrid methodologies including Shannon’s entropy, TOPSIS (the technique for order preference by similarity to ideal solution) and goal programming are respectively used for determining the weight of criteria which are effective in the inventory items classification, calculations of each item value and its classification based on Pareto’s principle. To this end, the value of each item as well as classification of inventory items is calculated based on Pareto’s principle. The performance of the proposed method is evaluated through (1) statistical analysis, (2) checking the percentage of similarity with other methods and (3) comparison with another method in terms of the number and value allocated to each class. The results confirm the capability of the listed method.read more
Citations
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Journal ArticleDOI
BBO-BPNN and AMPSO-BPNN for multiple-criteria inventory classification
TL;DR: This paper introduces biogeography-based optimization and an adaptive mutation particle swarm optimizer to BPNN to optimize the training parameters, i.e., the global initial connection weights and thresholds, of BPNN and demonstrates that BBO-BPNN and AMPSO- BPNN show higher classification accuracy than other hybrid models in the multiple-criteria inventory classification problem.
Journal ArticleDOI
A novel fuzzy mcdm model for inventory management in order to increase business efficiency
TL;DR: It has been determined based on an extensive sensitivity analysis that the developed models have better performance compared to the existing ones.
Journal ArticleDOI
PSO based data clustering with a different perception
TL;DR: In this article, a new dimension called family memory has been introduced to enhance PSO-based clustering's performance, wherein not only the data were clustered but also the particles.
Journal ArticleDOI
A New Method of Storage Management Based on ABC Classification: A Case Study in Chinese Supermarkets’ Distribution Center:
Hung-Lung Lin,Yu-Yu Ma +1 more
TL;DR: Most of the distribution centers of chain supermarkets in China adopt the excessively simple activity-based classification (ABC) as the management method of classifying warehousing work, which ofte...
Journal ArticleDOI
A hybrid fuzzy-stochastic multi-criteria ABC inventory classification using possibilistic chance-constrained programming.
TL;DR: A mathematical modeling-based approach is proposed considering different types of uncertainty in classification information and a hybrid algorithm based on chance-constrained and possibilistic programming is proposed to solve the problems.
References
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Journal ArticleDOI
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Journal ArticleDOI
ABC inventory classification with multiple-criteria using weighted linear optimization
TL;DR: A simple classification scheme is proposed in this paper using weighed linear optimization for inventory classification using ABC analysis and the methodology is illustrated using an example.
Journal ArticleDOI
A simple classifier for multiple criteria ABC analysis
TL;DR: A simple model for multiple criteria inventory classification is proposed that converts all criteria measures of an inventory item into a scalar score and can be widely applied to inventory managers with minimal backgrounds in optimization.