Decision model using hierarchical fuzzy TOPSIS: Towards improving decision making in food waste management

Mohd Faizal Omar, Junidah Abdul Shukor, Maznah Mat Kassim, Kasmaruddin Che Hussin

Abstract


Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) is based on decision model to measure alternative with shortest distance to positive ideal solution and the farthest distance from negative ideal solution. With growing complexity in decision making, vagueness and uncertainty often exist in human judgement. To manage conflicting criteria, a hierarchy structure in TOPSIS is proposed where the main criteria, sub-criteria, and alternatives are arranged in multi-level. To rate each alternatives, the weight of each criterion is evaluated using linguistic value before converted into fuzzy number as a way to measure the experts opinion. In this paper, we demonstrates our general framework for the development of hierarchal fuzzy TOPSIS. We also highlighted our initial finding on the criteria and alternatives in our case study i.e. selection of decomposition technology for food waste management. It is anticipates our work will contributes better decision making in the related area.

Keywords


Hierarchical Fuzzy TOPSIS; Linguistic Variable; Decomposition Technology; Food Waste

Full Text:

PDF

References


Tzeng, G. H., & Huang, J. J. (2011). Multiple attribute decision making: methods and applications. CRC press.

Kabir, G., & Hasin, M. (2012). Comparative Analysis of TOPSIS and FUZZY TOPSIS for the Evaluation of Travel Website Service Quality. International Journal for Quality Research, 6(3).

Ataei, E., & Branch, A. (2013). Application of TOPSIS and fuzzy TOPSIS methods for plant layout design. World Applied Sciences Journal, 24(7), 908-913.

Najafi, E., Molana, M. H., Sajadi, M., & Miri-Nargesi, S. (2016). A Hierarchical Fuzzy TOPSIS Methodology for Supplier Selection with a Case Study in Guilan Textile Industry.

Chen, C. T. (2000). Extensions of the TOPSIS for group decision-making under fuzzy environment. Fuzzy sets and systems, 114(1), 1-9.

Ashrafzadeh, M., Rafiei, F. M., Isfahani, N. M., & Zare, Z. (2012). Application of fuzzy TOPSIS method for the selection of Warehouse Location: A Case Study. Interdisciplinary journal of contemporary research in business, 3(9), 655-671.

Sevkli, M., Zaim, S., Turkyilmaz, A., & Satir, M. (2010, July). An application of fuzzy Topsis method for supplier selection. In International Conference on Fuzzy Systems, 1-7. IEEE.

Ranjbar, H. R., & Nekooie, M. A. (2018). An improved hierarchical fuzzy TOPSIS approach to identify endangered earthquake-induced buildings. Engineering Applications of Artificial Intelligence, 76, 21-39.

Roshandel, J., Miri-Nargesi, S. S., & Hatami-Shirkouhi, L. (2013). Evaluating and selecting the supplier in detergent production industry using hierarchical fuzzy TOPSIS. Applied mathematical modelling, 37(24), 10170-10181.

Liu, H. C., Wang, L. E., Li, Z., & Hu, Y. P. (2018). Improving risk evaluation in FMEA with cloud model and hierarchical TOPSIS method. IEEE Transactions on Fuzzy Systems, 27(1), 84-95.

Sopha, B. M., Asih, A. M. S., & Nursitasari, P. D. (2018). Location planning of urban distribution center under uncertainty: A case study of Yogyakarta Special Region Province, Indonesia. Journal of Industrial Engineering and Management (JIEM), 11(3), 542-568.

Bao, Q., Ruan, D., Shen, Y., Hermans, E., & Janssens, D. (2012). Improved hierarchical fuzzy TOPSIS for road safety performance evaluation. Knowledge-based systems, 32, 84-90.

Chu, T. C., & Lin, Y. (2009). An extension to fuzzy MCDM. Computers & Mathematics with Applications, 57(3), 445-454.

Kahraman, C., Ҫevik, S., & ӦztayŞi B. (2015). Fuzzy Multicriteria Desicion-Making: A Literature Review. Interdiscipolinary Journal of Computational Intelligence Systems, 8(4), 637 - 666.

Zadeh, L. A. (1975). The concept of a linguistic variable and its application to approximate reasoning—I. Information sciences, 8(3), 199-249.

Moayeri, M., Shahvarani, A., Behzadi, M. H., & Hosseinzadeh-Lotfi, F. (2015). Comparison of fuzzy AHP and fuzzy TOPSIS methods for math teachers selection. Indian Journal of Science and Technology, 8(13), 1.

Elomda, B. M., Hefny, H. A., & Hassan, H. A. (2013). An extension of fuzzy decision maps for multicriteria decision-making. Egyptian Informatics Journal, 14(2), 147-155.

Ye, F., & Li, Y. (2014). An extended TOPSIS model based on the possibility theory under fuzzy environment. Knowledge-Based Systems, 67, 263-269.

Kahraman, C., Ateş, N. Y., Çevik, S., Gülbay, M., & Erdoğan, S. A. (2007). Hierarchical fuzzy TOPSIS model for selection among logistics information technologies. Journal of Enterprise Information Management.

Zarbini-Sydani, A., Karbasi, A., & Atef-Yekta, E. (2011). Evaluating and selecting supplier in textile industry using hierarchical fuzzy TOPSIS. Indian Journal of Science and Technology, 4(10), 1322-1334.

Taghavifard, M.T., & Mirheydari, D. (2008). Prioritization of Suppliers using a Hierarchical Fuzzy TOPSIS. Indian Journal of Computer and Information Engineering, 2(5), 1749-1755.

Wang, X., & Chan, H. K. (2013). A hierarchical fuzzy TOPSIS approach to assess improvement areas when implementing green supply chain initiatives. International Journal of Production Research, 51(10), 3117-3130.

Sun, C. C. (2010). A performance evaluation model by integrating fuzzy AHP and fuzzy TOPSIS methods. Expert systems with applications, 37(12), 7745-7754.

Ding, J. F. (2011). An integrated fuzzy TOPSIS method for ranking alternatives and its application. Journal of Marine Science and Technology, 19(4), 341-352.

Baykasoğlu, A., Kaplanoğlu, V., Durmuşoğlu, Z. D., & Şahin, C. (2013). Integrating fuzzy DEMATEL and fuzzy hierarchical TOPSIS methods for truck selection. Expert Systems with Applications, 40(3), 899-907.

Ateş, N. Y., Çevik, S., Kahraman, C., Gülbay, M., & Erdoğan, S. A. (2006). Multi attribute performance evaluation using a hierarchical fuzzy TOPSIS method. In Fuzzy applications in industrial engineering, 537-572. Springer, Berlin, Heidelberg.

Kore, N. B., Ravi, K., & Patil, S. B. (2017). A simplified description of fuzzy TOPSIS method for multi criteria decision making. International Research Journal of Engineering and Technology (IRJET), 4(5), 2047-2050.

Masudin, I., & Saputro, T. E. (2016, February). Evaluation of B2C website based on the usability factors by using fuzzy AHP & hierarchical fuzzy TOPSIS. In IOP Conference Series: Materials Science and Engineering, 114(1), p. 012091. IOP Publishing.

Paksoy, T., Pehlivan, N. Y., & Kahraman, C. (2012). Organizational strategy development in distribution channel management using fuzzy AHP and hierarchical fuzzy TOPSIS. Expert Systems with Applications, 39(3), 2822-2841.

Wang, T. C., & Chang, T. H. (2007). Application of TOPSIS in evaluating initial training aircraft under a fuzzy environment. Expert Systems with Applications, 33(4), 870-880.

Nursal, A. T., Omar, M. F., Mohd Nawi, M. N., & Asri, M. A. N. M. (2016). Adoption of cloud based decision support system for building information modeling software selection. Advanced Science Letters, 22(5-6), 1310-1313.

Nursal, A. T., Omar, M. F., & Nawi, M. N. M. (2015). The design of TOPSIS4BIM decision support for building information modeling software selection. Jurnal Teknologi, 77(5).

Sulaiman, N. I. S., Ghazali, S., Zabidi, N. Z., Omar, M. F., & Alias, R. A. (2015). Analytical hierarchy process and Markov Chain in shared knowledge through social media. Jurnal Teknologi, 77(5).

Sulaiman, N. I. S., Ghazali, S., Alias, R. A., Omar, M. F., & Zabidi, N. Z. (2015, May). Multi attribute decision making assessment on knowledge sharing through social media. In 2015 International Symposium on Mathematical Sciences and Computing Research (iSMSC), 185-189, IEEE.

Omar, M. F., Mohd Nawi, M. N., & Nursal, A. T. (2014). Towards the significance of decision aid in Building Information Modeling (BIM) software selection process. In E3S Web of Conferences, 3, 1-6. EDP Sciences.

Nursal, A. T., Omar, M. F., & Nawi, M. N. M. (2014). An overview of emerging technologies in contemporary decision support system development. In AIP Conference Proceedings, 1635(1), 634-638. American Institute of Physics.

Shukor, J. A., Omar, M. F., Kasim, M. M., Jamaludin, M. H., & Naim, M. A. (2018). Assessment of composting technologies for organic waste management J. Assessment, 9(8).


Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Journal of Language and Linguistic Studies
ISSN 1305-578X (Online)
Copyright © 2005-2022 by Journal of Language and Linguistic Studies