Enhancing the Efficiency of Weighted Aggregated Sum Product Assessment Using Gibbs Entropy for Multi-Criteria Decision-Making Problems
DOI:
https://doi.org/10.14456/jeit.2025.2Keywords:
Multi-criteria decision making, WASPAS, Gibbs entropy, CNC machine selectionAbstract
Multi-Criteria Decision Making (MCDM) is a crucial approach in decision-making processes involving multiple factors. It is widely applied in various fields such as engineering, management, and logistics. The Weighted Aggregated Sum Product Assessment (WASPAS) technique is one of the most efficient MCDM methods, as it integrates the strengths of the Weighted Sum Model (WSM) and Weighted Product Model (WPM). However, a key limitation of WASPAS is the fixed assignment of the parameter =0.5, which may impact the accuracy of ranking alternatives. This study proposes a novel approach incorporating Gibbs Entropy to analyze the sensitivity of the
parameter and uses entropy values as a ranking criterion. The proposed method was tested on a Computer Numerical Control (CNC) lathe selection problem, demonstrating a high Spearman correlation coefficient (r) when compared with WASPAS (r =1.000) and COPRAS (r =0.937). These results confirm that the proposed method is highly reliable and produces rankings consistent with established MCDM techniques. This study can be applied to MCDM problems where parameter sensitivity analysis is necessary, enhancing decision-making accuracy and reliability.
References
[1] S. S. Goswami and D. K. Behera, "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, vol. 5, pp. 947–973, 2021.
DOI: 10.1007/s41660-021-00192-5.
[2] I. Ajripour, M. Asadpour, and L. Tabatabaie, "A model for organization performance management applying MCDM and BSC: A case study," Journal of Applied Research on Industrial Engineering, vol. 6, no. 1, pp. 52–70, 2019. DOI: 10.22105/jarie.2019.171886.1080.
[3] Z. Wen et al., "Cold chain logistics management of medicine with an integrated multi-criteria decision-making method," International Journal of Environmental Research and Public Health, vol. 16, no. 23, p. 4843, 2019.
DOI: 10.3390/ijerph16234843.
[4] D. G. B. de Souza, E. A. dos Santos, N. Y. Soma, and C. E. S. da Silva, "MCDM-based R&D project selection: A systematic literature review," Sustainability, vol. 13, no. 21, p. 11626, 2021.
DOI: 10.3390/su132111626.
[5] S. K. Sahoo and S. S. Goswami, "A comprehensive review of multiple criteria decision-making (MCDM) methods: Advancements, applications, and future directions," Decision Making Advances, vol. 1, no. 1, pp. 25–48, 2023.
DOI: 10.31181/dma1120237.
[6] S. Alvarez Gallo and J. Maheut, "Multi-criteria analysis for the evaluation of urban freight logistics solutions: A systematic literature review," Mathematics, vol. 11, no. 19, p. 4089, 2023. DOI: 10.3390/math11194089.
[7] E. K. Zavadskas, Z. Turskis, J. Antucheviciene, and A. Zakarevicius, "Optimization of weighted aggregated sum product assessment," Elektronika ir Elektrotechnika, vol. 122, no. 6, pp. 3–6, 2012. DOI: 10.5755/j01.eee.122.6.1810.
[8] N. Thongmual, C. Laoha, and N. Wichapa, "An optimistic-pessimistic game cross-efficiency method based on a Gibbs entropy model for ranking decision making units," Bulletin of Electrical Engineering and Informatics, vol. 13, no. 2, pp. 1411–1423, 2024.
DOI: 10.11591/eei.v13i2.5747.
[9] N. Wichapa, W. Khanthirat, and T. Sudsuansee, "A novel Gibbs entropy model based upon cross-efficiency measurement for ranking decision making units," Mathematical Modelling of Engineering Problems, vol. 9, no. 2, pp. 390–396, 2022.
DOI: 10.18280/mmep.090212.
[10] T. Lu and S. T. Liu, "Ranking DMUs by comparing DEA cross-efficiency intervals using entropy measures," Entropy, vol. 18, no. 12, p. 452, 2016.
DOI: 10.3390/e18120452.
[11] P. Kailomsom, P. Nasawat, W. Khunthirat, and W. Phuangpornpitak, "A hybrid method based on BWM and TOPSIS-LP model to assess computer numerical control machines," Engineering Access, vol. 11, no. 1, pp. 108–118, 2025.
DOI: 10.14456/mijet.2025.9.
[12] M. Zolfani, A. Zavadskas, M. Turskis, and Z. L. Saparauskas, "A hybrid MCDM model encompassing SWARA and WASPAS methods for supporting the contractor selection," Applied Soft Computing, vol. 25, pp. 1–9, 2014.
DOI: 10.1016/j.asoc.2014.07.014.
[13] S. Chakraborty, R. D. Raut, T. M. Rofin, and S. Chakraborty, "A narrative literature review on optimization of manufacturing processes using weighted aggregated sum product assessment (WASPAS) method," OPSEARCH, vol. 61, no. 4, pp. 1001–1022, 2024. DOI: 10.1007/s12597-024-00858-x.
[14] I. Otay et al., "Multi-criteria oil station location evaluation using spherical AHP & WASPAS: A real-life case study," in Intelligent and Fuzzy Techniques: Smart and Innovative Solutions, In C. Kahraman et al., Eds., Advances in Intelligent Systems and Computing, vol. 1197, Springer, Cham, 2020, pp. 591–598.
DOI: 10.1007/978-3-030-51156-2_68.
[15] C. L. Wang and K. Yoon, Multiple Attribute Decision Making: Methods and Applications, Springer, Berlin Heidelberg, 1981.
[16] E. K. Zavadskas, A. Kaklauskas, and V. Šarka, "The new method of multicriteria complex proportional assessment of projects," Technological and Economic Development of Economy, vol. 1, pp. 131–139, 1994.
[17] W. K. Brauers and E. K. Zavadskas, "The MOORA method and its application to privatization in a transition economy," Control and Cybernetics, vol. 35, no. 2, pp. 445–469, 2006.
[18] G. S. de Assis, M. dos Santos, and M. P. Basilio, "Use of the WASPAS method to select suitable helicopters for aerial activity carried out by the military police of the state of Rio de Janeiro," Axioms, vol. 12, no. 1, p. 77, 2023.
DOI: 10.3390/axioms12010077.
[19] M. Akram et al., "2-tuple linguistic Fermatean fuzzy MAGDM based on the WASPAS method for selection of solid waste disposal location," Mathematical Biosciences and Engineering, vol. 20, no. 2, pp. 3811–3837, 2023.
DOI: 10.3934/mbe.2023179.
[20] R. Lukić et al., "Application of WASPAS method in the evaluation of efficiency of agricultural enterprises in Serbia," Economics of Agriculture, vol. 68, no. 2, pp. 375–388, 2021.
DOI: 10.5937/ekopolj2102375l.
[21] E. K. Zavadskas et al., "Application of WASPAS method as an optimization tool in non-traditional machining processes," Information Technology and Control, vol. 44, no. 1, pp. 77–88, 2015.
DOI: 10.5755/j01.itc.44.1.7124.
Downloads
Published
How to Cite
Issue
Section
Categories
License
Copyright (c) 2025 Journal of Engineering and Industrial Technology, Kalasin University
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
ลิขสิทธิ์ของวารสาร
เนื้อหาและข้อมูลในบทความที่ลงตีพิมพ์ในวารสารศูนย์ดัชนีการอ้างอิงวารสารไทย ถือเป็นข้อคิดเห็นและความรับผิดชอบของผู้เขียนบทความโดยตรงซึ่งกองบรรณาธิการวารสาร ไม่จำเป็นต้องเห็นด้วย หรือร่วมรับผิดชอบใด ๆ
บทความ ข้อมูล เนื้อหา รูปภาพ ฯลฯ ที่ได้รับการตีพิมพ์ในวารสารศูนย์ดัชนีการอ้างอิงวารสารไทย ถือเป็นลิขสิทธิ์ของวารสารศูนย์ดัชนีการอ้างอิงวารสารไทย หากบุคคลหรือหน่วยงานใดต้องการนำทั้งหมดหรือส่วนหนึ่งส่วนใดไปเผยแพร่ต่อหรือเพื่อกระทำการใด จะต้องได้รับอนุญาตเป็นลายลักอักษรจากวารสารศูนย์ดัชนีการอ้างอิงวารสารไทยก่อนเท่านั้น
