Fuzzy sets, decision making and expert systems
Fuzzy sets, decision making and expert systems
Multicriteria decision analysis with fuzzy pairwise comparisons
Fuzzy Sets and Systems
Extensions of the TOPSIS for group decision-making under fuzzy environment
Fuzzy Sets and Systems
Fuzzy hierarchical analysis: the Lambda-Max method
Fuzzy Sets and Systems - Special issue on clustering and learning
Classifying inventory using an artificial neural network approach
Computers and Industrial Engineering
Deriving priorities from fuzzy pairwise comparison judgements
Fuzzy Sets and Systems - Optimisation and decision
The appropriate total ranking method using DEA for multiple categorized purposes
Journal of Computational and Applied Mathematics - Special issue: Papers presented at the 1st Sino--Japan optimization meeting, 26-28 October 2000, Hong Kong, China
A case-based distance model for multiple criteria ABC analysis
Computers and Operations Research
An integrated AHP-DEA methodology for bridge risk assessment
Computers and Industrial Engineering
ABC inventory classification with multiple-criteria using weighted linear optimization
Computers and Operations Research
Fuzzy least-squares priority method in the analytic hierarchy process
Fuzzy Sets and Systems
Multiple Criteria Inventory Classification Under Fuzzy Environment
International Journal of Fuzzy System Applications
Calibrated fuzzy AHP for current bank account selection
Expert Systems with Applications: An International Journal
| Hi-index | 12.05 |
In order to efficiently control the inventory items and determine the suitable ordering policies for them, multi-criteria ABC inventory classification, which is one of the most common techniques of production and inventory control, is used. In this classification, other criteria in addition to annual dollar usage are taken into account and then the items are classified in three classes with different ordering policies, based on their priority. In this paper, we propose an integrated fuzzy analytic hierarchy process-data envelopment analysis (FAHP-DEA) for multiple criteria ABC inventory classification. The proposed FAHP-DEA methodology uses the FAHP to determine the weights of criteria, linguistic terms such as Very High, High, Medium, Low and Very Low to assess each item under each criterion, the data envelopment analysis (DEA) method to determine the values of the linguistic terms, and the simple additive weighting (SAW) method to aggregate item scores under different criteria into an overall score for each item. The integrated FAHP-DEA methodology is illustrated using a real case study.