Application of the R method in solving material handling equipment selection problems


  • Saikat Chatterjee Department of Mechanical Engineering, Sikkim Manipal Institute of Technology, Sikkim Manipal University, Sikkim, India
  • Shankar Chakraborty Department of Production Engineering, Jadavpur University, Kolkata, India



Material handling equipment, Selection, MCDM, R method, Ranking


In manufacturing industries, material handling equipment plays a vital role and is considered as one of the important pillars to increase production efficiency. Hence, the selection of appropriate material handling equipment for a specific task is well acknowledged, but the complexity of this selection process drastically increases with the rise in the number of alternative equipment available in the market and a set of conflicting evaluation criteria. To resolve this problem, several multi-criteria decision-making (MCDM) techniques have been proposed by past researchers. In this paper, the application potentiality of a newly developed MCDM technique, i.e. R method is explored while solving five material handling equipment selection problems, i.e. conveyor, automated guided vehicle (AGV), stacker, wheel loader and excavator. The derived ranking results are contrasted with other popular MCDM techniques to validate its potentiality in shortlisting the candidate alternatives from the best to the worst, which would ultimately help in improving the overall efficiency of the manufacturing processes.


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Alosta, A., Elmansuri, O., & Badi, I. (2021). Resolving a location selection problem by means of an integrated AHP-RAFSI approach. Reports in Mechanical Engineering, 2(1), 135-142. DOI:

Agarwal, D., & Bharti, P. S. (2018). A case study on AGV’s alternatives selection problem. International Journal of Information Technology, 14(2),1011-1023.

Bairagi, B., Dey, B., Sarkar, B., & Sanyal, S. K. (2015). A De Novo multi-approaches multi-criteria decision making technique with an application in performance evaluation of material handling device. Computers & Industrial Engineering, 87, 267-282. DOI:

Biswas, T., Chatterjee, P., & Choudhuri, B. (2020). Selection of commercially available alternative passenger vehicle in automotive environment. Operational research in engineering sciences: theory and applications, 3(1), 16-27. DOI:

Bozanic, D., Tešić, D., Marinković, D., & Milić, A. (2021). Modeling of neuro-fuzzy system as a support in decision making processes. Reports in Mechanical Engineering, 2(1), 222-234. DOI:

Chakraborty, S., & Banik, D. (2006). Design of a material handling equipment selection model using analytic hierarchy process. The International Journal of Advanced Manufacturing Technology, 28(11), 1237-1245. DOI:

Chatterjee, S., & Chakraborty, S. (2022). A multi-attributive ideal-real comparative analysis-based approach for piston material selection. OPSEARCH, 59(1), 207-228.

Diakoulaki, D., Mavrotas, G., & Papayannakis, L. (1995). Determining objective weights in multiple criteria problems: The critic method. Computers & Operations Research, 22(7), 763-770. DOI:

Fazlollahtabar, H., & Kazemitash, N. (2021). Green supplier selection based on the information system performance evaluation using the integrated Best-Worst Method. Facta Universitatis, Series: Mechanical Engineering, 19(3), 345-360.

Feng, L. (2021). Multicriteria approach to the selection of the training model of dangerous goods transport advisors in the ministry of defense and the Serbian Army. Vojnotehnički glasnik, 69(4), 828-851.

Ghaleb, A. M., Kaid, H., Alsamhan, A., Mian, S. H., & Hidri, L. (2020). Assessment and comparison of various MCDM approaches in the selection of manufacturing process. Advances in Materials Science and Engineering, Article ID 4039253, 16 pages,

Goswami, S. S., & Behera, D. K. (2021). Solving Material Handling Equipment Selection Problems in an Industry with the Help of Entropy Integrated COPRAS and ARAS MCDM techniques. Process Integration and Optimization for Sustainability, 5(4), 947-973.

Hadi-Vencheh, A., & Mohamadghasemi, A. (2015). A new hybrid fuzzy multi-criteria decision making model for solving the material handling equipment selection problem. International Journal of Computer Integrated Manufacturing, 28(5), 534-550. DOI:

Horňáková, N., Jurík, L., Hrablik Chovanová, H., Cagáňová, D., & Babčanová, D. (2021). AHP method application in selection of appropriate material handling equipment in selected industrial enterprise. Wireless Networks, 27(3), 1683-1691.

Karande, P., & Chakraborty, S. (2013). Material handling equipment selection using weighted utility additive theory. Journal of Industrial Engineering, Article ID 268708, 9 pages, DOI:

Khandekar, A. V., & Chakraborty, S. (2015). Selection of material handling equipment using fuzzy axiomatic design principles. Informatica, 26(2), 259-282. DOI:

Kulak, O. (2005). A decision support system for fuzzy multi-attribute selection of material handling equipments. Expert systems with applications, 29(2), 310-319. DOI:

Maniya, K. D., & Bhatt, M. G. (2011). A multi-attribute selection of automated guided vehicle using the AHP/M-GRA technique. International Journal of Production Research, 49(20), 6107-6124. DOI:

Mathew, M., & Sahu, S. (2018). Comparison of new multi-criteria decision making methods for material handling equipment selection. Management Science Letters, 8(3), 139-150. DOI:

Nguyen, H. T., Md Dawal, S. Z., Nukman, Y., P. Rifai, A., & Aoyama, H. (2016). An integrated MCDM model for conveyor equipment evaluation and selection in an FMC based on a fuzzy AHP and fuzzy ARAS in the presence of vagueness. PloS one, 11(4), e0153222. DOI:

Prasad, K., Zavadskas, E. K., & Chakraborty, S. (2015). A software prototype for material handling equipment selection for construction sites. Automation in Construction, 57, 120-131. DOI:

Rahimdel, M. J., & Bagherpour, R. (2018). Haulage system selection for open pit mines using fuzzy MCDM and the view on energy saving. Neural Computing and Applications, 29(6), 187-199. DOI:

Rao, R. V. (2007). Decision making in the manufacturing environment: using graph theory and fuzzy multiple attribute decision making methods. (1st ed.). London: Springer. DOI:

Rao, R., & Lakshmi, J. (2021). R-method: A simple ranking method for multi-attribute decision-making in the industrial environment. Journal of Project Management, 6(4), 223-230.

Rao, R. V., & Lakshmi, R. J. (2021a). Ranking of Pareto-optimal solutions and selecting the best solution in multi-and many-objective optimization problems using R-method. Soft Computing Letters, 3, 100015.

Saputro, T. E., Masudin, I., & Daneshvar Rouyendegh, B. (2015). A literature review on MHE selection problem: levels, contexts, and approaches. International Journal of Production Research, 53(17), 5139-5152. DOI:

Saputro, T. E., & Daneshvar Rouyendegh, B. (2016). A hybrid approach for selecting material handling equipment in a warehouse. International Journal of Management Science and Engineering Management, 11(1), 34-48. DOI:

Satoglu, S. I., & Türkekul, İ. (2021). Selection of Material Handling Equipment using the AHP and MOORA. Jurnal Teknik Industri, 22(1), 113-124.

Srdjevic, B., Medeiros Y.D.P., Faria, A.S., & Schaer, M. (2003). Objektivno vrednovanje kriterijuma performance sistema akumulacija. Vodoprivreda, 35, 163-176, (only in Serbian).

Ulutaş, A., Karabasevic, D., Popovic, G., Stanujkic, D., Nguyen, P. T., & Karaköy, Ç. (2020). Development of a novel integrated CCSD-ITARA-MARCOS decision-making approach for stackers selection in a logistics system. Mathematics, 8(10), 1672-1684

Zou, Z. H., Yi, Y., & Sun, J. N. (2006). Entropy method for determination of weight of evaluating indicators in fuzzy synthetic evaluation for water quality assessment. Journal of Environmental sciences, 18(5), 1020-1023. DOI:



How to Cite

Chatterjee, S., & Chakraborty, S. (2023). Application of the R method in solving material handling equipment selection problems . Decision Making: Applications in Management and Engineering, 6(2), 74–94.