A New Hybrid Multi-criteria ABC Inventory Classification Model Based on Differential Evolution and Topsis

Cherif, Hedi; Ladhari, Talel

doi:10.1007/978-3-319-52941-7_9

Cited by 2 publications

(2 citation statements)

References 24 publications

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“…During the last decades, many companies have taken seriously the task of managing the inventory efficiently because of the surplus of stock and the need to make more profits for their financial and logistical well-being. For this purpose, the ABC classification is one of the most frequently used analyses in production and inventory management domains, in order to classify a set of items in the three predefined classes A, B, and C, where each class follows a specific management and control policies [12]. Efficient inventory classification is a vital activity for companies that handle large quantities of inventory.…”

Section: Abc Analysismentioning

confidence: 99%

A New Model for Stock Management in Order to Rationalize Costs: ABC-FUCOM-Interval Rough CoCoSo Model

et al. 2019

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Cost rationalization has become imperative in every economic system in order to create adequate foundations for its efficient and sustainable management. Competitiveness in the global market is extremely high and it is challenging to manage business and logistics systems, especially with regards to financial parameters. It is necessary to rationalize costs in all activities and processes. The presence of inventories is inevitability in every logistics system, and it tends to create adequate and symmetrical policies for their efficient and sustainable management. In order to be able to do this, it is necessary to determine which products represent the largest percentage share in the value of procurement, and which are the most represented quantitatively. For this purpose, ABC analysis, which classifies products into three categories, is applied taking into account different constraints. The aim of this paper is to form a new model that involves the integration of ABC analysis, the Full Consistency Method (FUCOM), and a novel Interval Rough Combined Compromise Solution (CoCoSo) for stock management in the storage system. A new IRN Dombi weighted geometric averaging (IRNDWGA) operator is developed to aggregate the initial decision matrix. After grouping the products into three categories A, B and C, it is necessary to identify appropriate suppliers for each category in order to rationalize procurement costs. Financial, logistical, and quality parameters are taken into account. The FUCOM method has been used to determine the significance of these parameters. A new Interval CoCoSo approach is developed to determine the optimal suppliers for each product group. The results obtained have been modeled throughout a multi-phase sensitivity analysis.

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Section: Abc Analysismentioning

confidence: 99%

A New Model for Stock Management in Order to Rationalize Costs: ABC-FUCOM-Interval Rough CoCoSo Model

et al. 2019

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“…The research (Hanafi et al, 2019) determined necessary items for the execution of the economic order quantity by applying the ABC analysis. Cherif and Ladhari (2016) created a hybrid model consisting of ABC classification using an evolutionary algorithm and the MCDM method. This research minimizes inventory management costs and ensures acceptable performance.…”

Section: Introductionmentioning

confidence: 99%

A Novel Fuzzy McDm Model for Inventory Management in Order to Increase Business Efficiency

Vukasović

Gligović

Terzić

et al. 2021

Technological and Economic Development of Economy

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A New Hybrid Multi-criteria ABC Inventory Classification Model Based on Differential Evolution and Topsis

Cited by 2 publications

References 24 publications

A New Model for Stock Management in Order to Rationalize Costs: ABC-FUCOM-Interval Rough CoCoSo Model

A New Model for Stock Management in Order to Rationalize Costs: ABC-FUCOM-Interval Rough CoCoSo Model

A Novel Fuzzy McDm Model for Inventory Management in Order to Increase Business Efficiency

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