A Multicriteria Decision-Making Model for Selecting Warehouse Rack Systems

Authors

  • Napat Srinual Department of Logistics and Transportation Management, Faculty of Logistics and Transportation Management, Panyapiwat Institute of Management
  • Nantawan Boonraksa Department of Logistics and Transportation Management, Faculty of Logistics and Transportation Management, Panyapiwat Institute of Management

Keywords:

Multicriteria Decision Making, Analytical Hierarchy Process, Neutrosophic Sets, Warehouse Rack Systems

Abstract

Selecting the right racking system in warehouses significantly affects costs, productivity, and efficiency. This decision is complex due to various subjective factors. This study proposes a multicriteria decision making approach combining the Analytical Hierarchy Process (AHP) with Neutrosophic Sets (NSs) to manage uncertainty, ambiguity, and indeterminacy in the decision-making process. The study employs an AHP-NS model to determine criteria weights and rank potential racking storage systems. Five options were evaluated: Selective, Double-reach, Drive-in, Drive-through, and Push-back racks. These were assessed based on four primary criteria and ten sub-criteria, identified through literature review and experts. Six decision-makers from diverse roles, including top management, finance, engineering, procurement, and operations, were selected using stratified random sampling. Their input was crucial in evaluating the alternatives against the established criteria. The results revealed that “Speed” was the most critical factor, accounting for 37% of the decision weight, followed by utilization, cost, and type of access. Interestingly, LIFO and FIFO access methods were ranked least important at 3% and 4%, respectively. The Selective racking system emerged as the top choice, scoring 75% overall. This comprehensive approach offers a structured method for warehouse managers to make informed decisions on racking systems, considering multiple factors and stakeholder perspectives.

References

Chan, F. T. S. (2002). Design of material handling equipment selection system: An integration of expert system with analytic hierarchy process approach. Integrated Manufacturing Systems, 3(1), 58-68. https://shorturl.asia/IZnPN

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. https://shorturl.asia/24scd

Dua, T. V. (2023). Forklift selection by multi-criteria decision-making methods. Eastern-European Journal of Enterprise Technologies, 5(3), 95–101. https://shorturl.asia/y271a

He, M., Guan, Z., Wang, C. & Hou, G. (2023). Multiple-Rack Strategies Using Optimization of Location Assignment Based on MRCGA in Miniload Automated Storage and Retrieval System. Processes, 11(3), 950. https://doi.org/10.3390/pr11030950

Jun, Y. (2014). A multi criteria decision-making method using aggregation operators for simplified Neutrosophic Sets. Journal of Intelligent & Fuzzy Systems, 26(5), 2459-2466.

https://doi.org/10.3233/IFS-130916

Kučera, T., (2019). Application of the activity-based costing to the logistics cost calculation for warehousing in the automotive industry. Communications-Scientific Letters of the University of Zilina, 21(4), 35–42. https://shorturl.asia/Y5NRP

Majumdar, P. (2015). Neutrosophic sets and its applications to decision making. In D. P. Acharjya, S. Dehuri, S. Sanyal. (Eds.). Computational Intelligence for Big Data Analysis: Frontier Advances and Applications (pp. 97–115). Springer. https://shorturl.asia/RuFan

Ming, Z. & Zheng, W. (2024). Optimizing rack locations in the mobile-rack picking system: A method of integrating rack heat and relevance, Mathematics, 12(3), 413. https://shorturl.asia/zx4kp

Mumali, F. & Kałkowska, J. (2023). Intelligent support in manufacturing process selection based on artificial neural networks, fuzzy logic, and genetic algorithms: Current State and future perspectives. Computers & Industrial Engineering, 193, 1-20. https://shorturl.asia/LnP2l

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), 1-26. https://shorturl.asia/XLDNH

Nirmala, I. (2024). FIFO Method Improvement and Adjustment Design for PT. ABC Warehouse Plans. Journal Ilmiah Manajemen Kesatuan, 12(3), 637–648. https://shorturl.asia/zw5VS

Onut, S., Kara, S. S. & Mert, S. (2009). Selecting the suitable material handling equipment in the presence of vagueness. The International Journal of Advanced Manufacturing Technology, 44, 818–828. https://shorturl.asia/sxae4

Patel, H. N., Parmar,M. & Bhavsar, D. (2022). Various types of material handling system. The International Journal of Creative Research Thoughts, 10(3), 42-69. https://shorturl.asia/qkQ1A

Pruša, P., Jovčić, S., Nemec, V. & Mrázek, P. (2018). Forklift truck selection using TOPSIS method. International Journal for Traffic and Transport Engineering, 8(3), 290-398. https://shorturl.asia/Hkcwr

Radwan,N., Senousy, M. B. & Riad, M. (2016). Neutrosophic Logic Approach for Evaluating Learning Management. Neutrosophic Sets and Systems, 11, 3-7. https://shorturl.asia/1Rfvq

Sabnis, D., Patil, M., & Wankhede, S. (2024). Selection of automated guided vehicles for industrial application using weighted sum method. Lecture notes in electrical engineering, 357–365. https://shorturl.asia/cG5K2

Safronov, E. & Nosko, A. (2019). A method to determine allowable speed for a unit load in a pallet flow rack. Acta Mechanica et Automatica, 13(2), 80-85. https://doi.org/10.2478/ama-2019-0011

Satoglu, S. I. & Türkekul, I. (2021). Selection of material handling equipment using the AHP and MOORA. Journal Teknik Industry, 22(1), 113-124. https://shorturl.asia/t7qvn Sequeira, A. A. (2019). A mathematical programming model to determine a suitable pallet storage system to improve storage space utilization. Journal of Research and Development, 4(1), 50-61. https://doi.org/10.12816/0052834

Setiyani, D .R. & Sukarno, I. (2022). Material handling equipment selection using Analytical Hierarchy Process (AHP) method. Journal Logistics Indonesia, 6(2), 91- 100. https://shorturl.asia/45FYe

Shin, D. Y., Lee, J. & Seok, H. (2023). A study of layout determination of mobile rack warehouse. AIMS Environmental Science, 10(4), 467-477. https://shorturl.asia/hUK3N

Soufi, Z., David, P. & Yahouni, Z. (2021). A methodology for the selection of material handling equipment in manufacturing systems. IFAC-PapersOnLine, 54(1), 122-127. https://shorturl.asia/uDy7g

Ulutaş, A., Topal, A., Karabasevic, D. & Balo, F. (2023). Selection of a forklift for a cargo company with Fuzzy BWM and Fuzzy MCRAT methods. Axioms, 12(5), 467. https://shorturl.asia/4tl1O

Wang, H., Smarandache, F., Zhang, Y., & Sunderraman, R. (2010). Single valued neutrosophic sets. In F. Smarandache (Eds.). Neutrosophic Transdisciplinarity (100 Collected Papers of Sciences) (Vol. IV, pp. 410-413)., North-European Scientific. https://shorturl.asia/UZSvd

Xu, Z. & Liao, H. (2014). Intuitionistic fuzzy analytic hierarchy process. IEEE Transactions on Fuzzy Systems, 22(4), 749-761. https://shorturl.asia/9wqWD

Yanling, Z., Yun, Z., Hassini, E., Yufei, Y., & Xiangpei, H. (2022). Rack retrieval and repositioning optimization problem in robotic mobile fulfillment systems. Transportation Research Part E: Logistics and Transportation Review, 167, 102920. https://doi.org/10.1016/j.tre.2022.102920

Zadeh, L. A. (1975). Fuzzy logic and approximate reasoning (In Memory of Grigore Moisil). Synthese, 30(3/4), 407-428. https://www.jstor.org/stable/20115038

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Published

2025-06-30

How to Cite

Srinual, N., & Boonraksa, N. . (2025). A Multicriteria Decision-Making Model for Selecting Warehouse Rack Systems . Business Administration and Management Journal Review, 17(1), 271–290. retrieved from https://so01.tci-thaijo.org/index.php/bahcuojs/article/view/275913

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Research Articles