Applying a hybrid MCDM technique in warehouse management




Warehouse Management, Best-Worst Method (BMW), Analytical Hierarchy Process (AHP), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), Multi-Criteria Decision Making (MCDM)


The main goal of this study is to apply Multi-Criteria Decision Making (MCDM) in managing a warehouse. One of the elements that could impact organization performance is warehouse management. Surplus inventory imposes some ad- ditional costs on the organization, and inadequate inventory stops the operation of an organization. For managing and controlling warehouse inventories, the MCDM method is recommended in this study. The inventories are categorized ba- sed on multi-criteria instead of a single criterion in ABC. To specify the criteria’s weight, Best-Worst Method is used, and to reach the final score of spare parts, the Analytical Hierarchy Process, and Technique for Order of Preference by Similarity to Ideal Solution is applied. Some strategies for managing and controlling organizations’ warehouse is recommended.


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Author Biography

Iman Ajripour, University of Miskolc

PhD candidate


Ajripour, I. (2020). Applying MCDM Technique in analyzing the effect of promotion items based on online shopping factors: A case study. In Udvari B. (Ed.), Proceedings of the European Union’s Contention in the Reshaping Global Economy (pp. 9-27). The University of Szeged, Doctoral School in Economics, Szeged.

Ajripour, I., & Alamian, R. (2021). Comparing Green Economy in Iran with OECD Asian Countries by Applying TOPSIS and GI Method. Theory Methodology Practice, 17(1), 15-26.

Ajripour, I., Asadpour, M., & Tabatabaie, L. (2019). A model for organization performance management applying MCDM and BSC: a case study. Journal of Applied Research on Industrial Engineering, 6(1), 52- 70.

Amiri, M., Tabatabaei, M. H., Ghahremanloo, M., Keshavarz-Ghorabaee, M., Zavadskas, E. K., &

Antucheviciene, J. (2020). A new fuzzy approach based on BWM and fuzzy preference programming for hospital performance evaluation: A case study. Applied Soft Computing, 92, 106279.

Antosz, K., & Ratnayake, R. C. (2016). Classification of spare parts as the element of a proper realization of the machine maintenance process and logistics-case study. IFAC-Papers OnLine, 49(12), 1389-1393.

Antosz, K., & Ratnayake, R. C. (2019). Spare parts’ criticality assessment and prioritization for enhancing manufacturing systems’ availability and reliability. Journal of Manufacturing Systems, 50, 212- 225.

Aragonés-Beltrán, P., Chaparro-González, F., Pastor- Ferrando, J. P., & Pla-Rubio, A. (2014). An AHP (Analytic Hierarchy Process)/ANP (Analytic Network Process)-based multi-criteria decision approach for the selection of solar-thermal power plant investment projects. Energy, 66, 222-238.

Balaji, K., & Kumar, V. S. (2014). Multicriteria inventory ABC classification in an automobile rubber components manufacturing industry. Procedia CIRP, 17, 463-468.

Bhattacharya, A., Sarkar, B., & Mukherjee, S. K. (2007). Distance-based consensus method for ABC analysis. International Journal of Production Research, 45(15), 3405-3420.

Braglia, M., Grassi, A., & Montanari, R. (2004). Multiattribute classification method for spare parts inventory management. Journal of Quality in Maintenance Engineering, 10(1), 55-65.

Cakir, O., & Canbolat, M. S. (2008). A web-based decision support system for multi-criteria inventory classification using fuzzy AHP methodology. Expert Systems with Applications, 35(3), 1367-1378.

Chatzimouratidis, A. I., & Pilavachi, P. A. (2009). Technological, economic, and sustainability evaluation of power plants using the Analytic Hierarchy Process. Energy Policy, 37(3), 778-787.

Chen, J. X. (2012). Multiple criteria ABC inventory classification using two virtual items. International Journal of Production Research, 50(6), 1702-1713.

Cohen, M. A., & Ernst, R. (1988). Multi-item classification and generic inventory stock control policies. Production and Inventory Management Journal, 29(3), 6–8.

Cui, L., Tao, Y., Deng, J., Liu, X., Xu, D., & Tang, G. (2021). BBO-BPNN and AMPSO-BPNN for multiplecriteria inventory classification. Expert Systems with Applications, 175, 114842.

Duchessi, P., Tayi, G.K., & Levy, J.B. (1988). A conceptual approach for managing of spare parts. International Journal of Physical Distribution & Materials Management, 18(5), 8-15.

Duran, O. (2015). Spare parts criticality analysis using a fuzzy AHP approach. Technical Gazette, 22(4), 899- 905.

Ecer, F., & Pamucar, D. (2020). Sustainable supplier selection: A novel integrated fuzzy best-worst method (F-BWM) and fuzzy COCOSO with Bonferroni (COCOSO’B) multi-criteria model. Journal of Cleaner Production, 266, 121981.

Ferreira, L. M. D., Maganha, I., Magalhães, V.S.M., & Almeida, M. (2018). A Multicriteria Decision Framework for the Management of Maintenance Spares – A Case Study. IFAC-PapersOnLine, 51(11), 531-537.

Flores, B. E., & Whybark, D. C. (1987). Implementing multiple criteria ABC analysis. Journal of Operations Management, 7(1-2), 79-85.

Gajpal, P. P., Ganesh, L. S., & Rajendran, C. (1994). Criticality analysis of spare parts using the analytic hierarchy process. International Journal of Production Economics, 35(1-3), 293-297.

Gong, J., Luo, Y., Qiu, Z., & Wang, X. (2020). Determination of key components in automobile braking systems based on ABC classification and FMECA. Journal of Traffic and Transportation Engineering (English Edition), 9(1), 69-77.

Gupta, H. (2018). Assessing organizations performance on the basis of GHRM practices using BWM and Fuzzy TOPSIS. Journal of Environmental Management, 226, 201–216.

Gupta, H., & Barua, M. K. (2017). Supplier selection among SMEs on the basis of their green innovation ability using BWM and fuzzy TOPSIS. Journal of Cleaner Production, 152, 242–258.

Hadi-Vencheh, A. (2010). An improvement to multiple criteria ABC inventory classification. European Journal of Operational Research, 201(3), 962-965.

Hadi-Vencheh, A., & Mohamadghasemi, A. (2011). A fuzzy AHP-DEA approach for multiple criteria ABC inventory classification. Expert Systems with Applications, 38(4), 3346-3352.

Han, M. L., Liou, J. M., Ser, K. H., Chen, J. C., Chen, S. C., & Lee, W. J. (2020). Changes of serum pepsinogen level and ABC classification after bariatric surgery. Journal of the Formosan Medical Association, 120(6), 1377-1385.

Hatefi, S. M., Torabi, S. A., & Bagheri, P. (2014). Multi-criteria ABC inventory classification with mixed quantitative and qualitative criteria. International Journal of Production Research, 52(3), 776–786. 00207543.2013.838328

Hwang, C. L., & Yoon, K. (1981). Multiple Attributes Decision Making Methods and Applications. New York: Springer.

Kaabi, H., Jabeur, K., & Ladhari, T. (2018). A genetic algorithm- based classification approach for multicriteria ABC analysis. International Journal of Information Technology & Decision Making, 17(06), 1805-1837.

Kheybari, S., Naji, S. A., Rezaie, F. M., & Salehpour, R. (2019). ABC classification according to Pareto’s principle: a hybrid methodology. Opsearch, 56(2), 539-562.

Kundrak, J., Molnar, V., & Deszpoth, I. (2018). Analysis of Machining Time and Material Removal Performance as Factors Influencing Efficiency and Profitability. In Vehicle and Automotive Engineering (pp. 268-279). Cham: Springer.

Li, J., Wang, J. Q., & Hu, J. H. (2019). Multi-criteria decision- making method based on dominance degree and BWM with probabilistic hesitant fuzzy information. International Journal of Machine Learning and Cybernetics, 10(7), 1671–1685.

Liu, Q., Huang, D. (2006, October). Classifying ABC inventory with multicriteria using a data envelopment analysis approach. In Sixth International Conference on Intelligent Systems Design and Applications (Vol. 1, pp. 1185- 1190). New York: IEEE.

Lo, H. W., Liou, J. J., Wang, H. S., & Tsai, Y. S. (2018). An integrated model for solving problems in green supplier selection and order allocation. Journal of Cleaner Production, 190, 339–352.

Lolli, F., Ishizaka, A., & Gamberini, R. (2014). New AHPbased approaches for multi-criteria inventory classification. International Journal of Production Economics, 156, 62-74.

Maghsoodi, A. I., Mosavat, M., Hafezalkotob, A., & Hafezalkotob, A. (2019). Hybrid hierarchical fuzzy group decision- making based on information axioms and BWM: Prototype design selection. Computers & Industrial Engineering, 127, 788–804.

Mei, M., & Chen, Z. (2021). Evaluation and selection of sustainable hydrogen production technology with hybrid uncertain sustainability indicators based on rough-fuzzy BWM-DEA. Renewable Energy, 165(Part1), 716-730.

Mikhailov, L. (2004). Group prioritization in the AHP by fuzzy preference programming method. Computers & Operations Research, 31(2), 293-301.

Molenaers, A., Baets, H., Pintelon, L., & Waeyenbergh, G. (2012). Criticality classification of spare parts: A case study. International Journal of Production Economics, 140(2), 570-578.

Molnar, V., & Horvath, D.D. (2017). Determination of Coefficients of Multi-Attribute Utility Function with Attribute Breakdown. In Proceedings of the 12th International Conference on Strategic Management and its Support by Information Systems (pp. 312-319). Ostrava, 2017.05.25. – 2017.05.26.

Momeni, M. (2010). New Topics in Operations Research. Tehran: Author publisher (In Persian Language). Mou, Q., Xu, Z. S., & Liao, H. C. (2016). An intuitionistic fuzzy multiplicative best-worst method for multi-criteria group decision making. Information Sciences, 374, 224–239.

Mou, Q., Xu, Z. S., & Liao, H. C. (2017). A graph based group decision-making approach with intuitionistic fuzzy preference relations. Computers & Industrial Engineering, 110, 138–150.

Ng, W. L. (2007). A simple classifier for multiple criteria ABC analysis. European Journal of Operational Research, 177(1), 344-353.

Nurcahyo, R., & Malik, F. M. (2017). Aircraft spare parts inventory management using multi-criteria classification with AHP approach. In 2017 4th IEEE International Conference on Engineering Technologies and Applied Sciences (ICETAS) (pp. 1-5). New York: IEEE.

Pamučar, D., Puška, A., Stević, Ž., & Ćirović, G. (2021). A new intelligent MCDM model for HCW management: The integrated BWM–MABAC model based on D numbers. Expert Systems with Applications, 175, 114862.

Partovi, F. Y., & Anandarajan, M. (2002). Classifying inventory using an artificial neural network approach. Computers & Industrial Engineering, 41(4), 389–404. https://doi. org/10.1016/s0360-8352(01)00064-x

Partovi, F. Y., Burton, J. (1993). Using the analytic hierarchy process for ABC analysis. International Journal of Operations & Production Management, 13(9), 29-44.

Ramanathan, R. (2006). ABC inventory classification with multiple criteria using weighted linear optimization. Computers and Operations Research, 33(3), 695–700.

Reid, R. A. (1987). The ABC method in hospital inventory management a practical. Production and Inventory Management Journal, 28(4), 67.

Rezaei, J. (2007). A fuzzy model for multi-criteria inventory classification. Analysis of Manufacturing Systems, 167- 172.

Rezaei, J. (2015). Best-worst multi-criteria decision-making method. Omega, 53, 49–57.

Rezaei, J., Esmaeilzadeh, M. (2007). Comparison of Different Multi-attribute Inventory ABC Classification Methods. Journal of Industrial Management Studies, 6(17), 1-22 (In Persian).

Rezaei, J., Nispeling, T., Sarkis, J., & Tavasszy, L. (2016). A supplier selection life cycle approach integrating traditional and environmental criteria using the best worst method. Journal of Cleaner Production, 135, 577–588.

Roda, I., Macchi, M., Fumagalli, L., & Viveros, P. (2012). On the classification of spare parts with a multi-criteria perspective. IFAC Proceedings Volumes, 45(31), 19-24.

Roszkowska, E. (2011). Multi-criteria decision-making models by applying the TOPSIS method to crisp and interval data. Multiple Criteria Decision Making/the University of Economics in Katowice, 6(1), 200-230.

Sedghiyan, D., Ashouri, A., Maftouni, N., Xiong, Q., Rezaee, E., & Sadeghi, S. (2021). Prioritization of renewable energy resources in five climate zones in Iran using AHP, hybrid AHP-TOPSIS, and AHP-SAW methods. Sustainable Energy Technologies and Assessments, 44, 101045.

Shahin, A., & Gholami, M. (2014). Spare Parts Inventory Classification Using Multi-Criteria Decision Making and Risk Priority Number. Case Study in Borzuyeh Petrochemical Company. Industrial Engineering, and Management Conference (In Persian).

Sharma, V., Kumar, A., & Kumar, M. (2021). A framework based on BWM for big data analytics (BDA) barriers in manufacturing supply chains. Materials Today: Proceedings, 47(16), 5515-5519.

Sindhu, S., Nehra, V., & Luthra, S. (2017). Investigation of feasibility study of solar farms deployment using hybrid AHP-TOPSIS analysis: Case study of India. Renewable and Sustainable Energy Reviews, 73, 496-511.

Stoll, J., Kopf, R., Schneider, J., & Lanza, G. (2015). Criticality analysis of spare parts management: a multi-criteria classification regarding a cross-plant central warehouse strategy. Production Engineering, 9(2), 225-235.

Syntetos, A. A., Keyes, M., & Babai, M. Z. (2009). Demand categorisation in a European spare parts logistics network. International Journal of Operations & Production Management, 29(3), 292-316.

Teixeira, C., Lopes, I., & Figueiredo, M. (2017). Multi-criteria classification for spare parts management: a case study. Procedia Manufacturing, 11, 1560-1567.

Torkayesh, A. E., Pamucar, D., Ecer, F., & Chatterjee, P. (2021). An integrated BWM-LBWA-CoCoSo framework for evaluation of healthcare sectors in Eastern Europe. Socio-Economic Planning Sciences, 78, 101052.

Ye, C., Li, K. W., Kilgour, D. M., & Hipel, K. W. (2008). A case-based distance model for multiple criteria ABC analysis. Computers & Operations Research, 35(3), 776–796.

You, P., Guo, S., Zhao, H., & Zhao, H. (2017). Operation performance evaluation of power grid enterprise using a hybrid BWM-TOPSIS method. Sustainability, 9(12), 2329.

Zeng, Y. R. & Wang, L. (2012). A Novel Approach for Evaluating Control Criticality of Spare Parts Using Fuzzy Comprehensive Evaluation and GRA. International Journal of Fuzzy Systems, 14(3).

Zhao, H., Guo, S., & Zhao, H. (2019). Comprehensive assessment for battery energy storage systems based on fuzzy-MCDM considering risk preferences. Energy, 168, 450–461.

Zhou, P., Fan, L. (2007). A note on multi-criteria ABC inventory classification using weighted linear optimization. European Journal of Operational Research, 182(3), 1488-1491.

Zowid, F. M., Babai, M. Z., Douissa, M. R., & Ducq, Y. (2019). Multi-criteria inventory ABC classification using Gaussian Mixture Model. IFAC-PapersOnLine, 52(13), 1925–1930.




How to Cite

Ajripour, I. (2022). Applying a hybrid MCDM technique in warehouse management. Vezetéstudomány / Budapest Management Review, 53(11), 55–68.