A Hybrid Multi-Criteria Analysis Model for Solving the Facility Location–Allocation Problem: A Case Study of Infectious Waste Disposal

Narong Wichapa, Porntep Khokhajaikiat


Choosing locations for infectious waste disposal (IWD) is one of the most significant issues in hazardous waste management due to the risk imposed on the environment and human life. This risk can be the result of an undesirable location of IWD facilities. In this study a hybrid multi-criteria analysis (Hybrid MCA) model for solving the facility location–allocation (FLA) problem for IWD was developed by combining two objectives: total cost minimization and weight maximization. Based on an actual case of forty-seven hospitals and three candidate municipalities in the northeastern region of Thailand, first, the Fuzzy AHP and Fuzzy TOPSIS techniques were integrated to determine the closeness of the coefficient weights of each candidate municipality. After that, these weights were converted to weighting factors and then these factors were taken into the objective function of the FLA model. The results showed that the Hybrid MCA model can help decision makers to locate disposal centers, hospitals and incinerator size simultaneously. Besides that the model can be extended by incorporating additional selection criteria/objectives. Therefore, it is believed that it can also be useful for addressing other complex problems.


facility location–allocation problem; Fuzzy AHP; Fuzzy TOPSIS; infectious waste disposal; multi-criteria decision making

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Askarian, M., Heidarpoor, P. & Assadian, O., A Total Quality Management Approach to Healthcare Waste Management in Namazi Hospital, Iran. Waste Manag, 30(11), pp. 2321-6, 2010.

Makajic-Nikolic, D., Petrovic, N., Belic, A., Rokvic, M., Radakovic, J.A. & Tubic, V., The Fault Tree Analysis of Infectious Medical Waste Management, Journal of Cleaner Production, 113, pp. 365-373, 2016.

Hansakul, A., Pitaksanurat, S., Srisatit, T. & Surit, P., Infectious Waste Management in the Government Hospitals By Private Transport Sector: Case Study of Hospitals in the North East of Thailand, Journal of Environmental Research and Development, 4(4), pp. 1070-1077, 2010.

He, T., Ho, W., Lee Ka Man, C. & Xu, X., A fuzzy AHP based Integer Linear Programming Model for the Multi-Criteria Transshipment Problem, The International Journal of Logistics Management, 23(1), pp. 159-179, 2012.

Lima Junior, F.R., Osiro, L. & Carpinetti, L.C.R., A Comparison between Fuzzy AHP and Fuzzy TOPSIS Methods to Supplier Selection, Applied Soft Computing, 21, pp. 194-209, 2014.

Nazam, M., Xu, J., Tao, Z., Ahmad, J. & Hashim, M., A Fuzzy AHP-TOPSIS Framework for the Risk Assessment of Green Supply Chain Implementation in the Textile Industry, International Journal of Supply and Operations Management, 2(1), pp. 548-568, 2015.

Wichapa, N. & Khokhajaikiat, P., Solving Multi-objective Facility Location Problem Using the Fuzzy Analytical Hierarchy Process and Goal Programming: A Case Study on Infectious Waste Disposal Centers, Operations Research Perspectives, 4, pp. 39-48, 2017.

Sirisawat, P. & Kiatcharoenpol, T., Fuzzy AHP-TOPSIS Approaches to Prioritizing Solutions for Reverse Logistics Barriers, Computers & Industrial Engineering, 117, pp. 303-318, 2018.

Kubler, S., Robert, J., Derigent, W., Voisin, A. & Le Traon, Y., A State-of-the-Art Survey & Testbed of Fuzzy AHP (FAHP) Applications, Expert Systems with Applications, 65, pp. 398-422, 2016.

Taylan, O., Bafail, A.O., Abdulaal, R.M.S. & Kabli, M.R., Construction Projects Selection and Risk Assessment by Fuzzy AHP and Fuzzy TOPSIS Methodologies, Applied Soft Computing, 17, pp. 105-116, 2014.

Büyüközkan, G. & Çifçi, G., A Combined Fuzzy AHP and Fuzzy TOPSIS based Strategic Analysis of Electronic Service Quality in Healthcare Industry, Expert Systems with Applications, 39(3), pp. 2341-2354, 2012.

Ertuğrul, İ. & Karakaşoğlu, N., Comparison of Fuzzy AHP and Fuzzy TOPSIS Methods for Facility Location Selection, The International Journal of Advanced Manufacturing Technology, 39(7), pp. 783-795, 2008.

Önüt, S., Efendigil, T. & Soner Kara, S., A Combined Fuzzy MCDM Approach for Selecting Shopping Center Site: An Example From Istanbul, Turkey, Expert Systems with Applications, 37(3), pp. 1973-1980, 2010.

Farahani, R.Z., SteadieSeifi, M. & Asgari, N., Multiple Criteria Facility Location Problems: A Survey, Applied Mathematical Modelling, 34(7), pp. 1689-1709, 2010.

Bai, X. & Liu, Y., Minimum Risk Facility Location-Allocation Problem with Type-2 Fuzzy Variables, The Scientific World Journal, 2014, pp. 472623, 2014.

Cooper, L., Location-Allocation Problems, Operations Research, 11(3), pp. 331-343, 1963.

Zhou, J. & Liu, B., Modeling Capacitated Location–Allocation Problem with Fuzzy Demands, Computers & Industrial Engineering, 53(3), pp. 454-468, 2007.

Hakimi, S.L., Optimum Distribution of Switching Centers in A Communication Network and Some Related Graph Theoretic Problems, Operations Research, 13(3), pp. 462-475, 1965.

Ernst, A.T. & Krishnamoorthy, M., Solution Algorithms for the Capacitated Single Allocation Hub Location Problem, Annals of Operations Research, 86, pp. 141-159, 1999.

Nozick, L.K. & Turnquist, M.A., A Two-Echelon Inventory Allocation and Distribution Center Location Analysis, Transportation Research Part E: Logistics and Transportation Review, 37(6), pp. 425-441, 2001.

Chan, Y., Mahan, J.M., Chrissis, J.W., Drake, D.A. & Wang, D., Hierarchical Maximal-Coverage Location–Allocation: Case of Generalized Search-And-Rescue, Computers & Operations Research, 35(6), pp. 1886-1904, 2008.

Altınel, İ.K., Durmaz, E., Aras, N. & Özkısacık, K.C., A Location–Allocation Heuristic for the Capacitated Multi-Facility Weber Problem with Probabilistic Customer Locations, European Journal of Operational Research, 198(3), pp. 790-799, 2009.

Yao, Z., Lee, L.H., Jaruphongsa, W., Tan, V. & Hui, C.F., Multi-Source Facility Location–Allocation and Inventory Problem, European Journal of Operational Research, 207(2), pp. 750-762, 2010.

Doolun, I.S., Ponnambalam, S.G., Subramanian, N. & G.K., Data Driven Hybrid Evolutionary Analytical Approach for Multi Objective Location Allocation Decisions: Automotive Green Supply Chain Empirical Evidence, Computers & Operations Research, 98, pp. 265-283, 2018.

Zhang, W., Cao, K., Liu, S. & Huang, B., A Multi-Objective Optimization Approach for Health-Care Facility Location-Allocation Problems in Highly Developed Cities such as Hong Kong. Computers, Environment and Urban Systems, 59, pp. 220-230, 2016.

Ghodratnama, A., Tavakkoli-Moghaddam, R. & Azaron, A., Robust and Fuzzy Goal Programming Optimization Approaches for a Novel Multi-Objective Hub Location–Allocation Problem: A Supply Chain Overview, Applied Soft Computing, 37, pp. 255-276, 2015.

Hussain, M., Awasthi, A. & Tiwari, M.K., Interpretive Structural Modeling-Analytic Network Process Integrated Framework for Evaluating Sustainable Supply Chain Management Alternatives, Applied Mathematical Modelling, 40(5-6), pp. 3671-3687, 2016.

Chaudhary, P., Chhetri, S.K., Joshi, K.M., Shrestha, B.M. & Kayastha, P., Application Of An Analytic Hierarchy Process (AHP) in the GIS Interface for Suitable Fire Site Selection: A Case Study from Kathmandu Metropolitan City, Nepal, Socio-Economic Planning Sciences, 53, pp. 60-71, 2016.

Bilbao-Terol, A., Arenas-Parra, M., Cañal-Fernández, V. & Antomil-Ibias, J., Using TOPSIS For Assessing the Sustainability of Government Bond Funds, Omega, 49, pp. 1-17, 2014.

Zadeh, L.A., Fuzzy Sets, Information and Control, 8(3), pp. 338-353, 1965.

Alavi, I., Fuzzy AHP Method for Plant Species Selection in Mine Reclamation Plans: Case Study Sungun Copper Mine, Iranian Journal of Fuzzy Systems, 11(5), pp. 23-38, 2014.

Rafiee, R., Ataei, M. & Jalali, S.M.E., The Optimum Support Selection by Using Fuzzy Analytical Hierarchy Process Method for Beheshtabad Water Transporting Tunnel in Naien, Iranian Journal of Fuzzy Systems, 10(6), pp. 39-51, 2013.

Nezarat, H., Sereshki, F. & Ataei, M., Ranking of Geological Risks in Mechanized Tunneling by Using Fuzzy Analytical Hierarchy Process (FAHP), Tunnelling and Underground Space Technology, 50, pp. 358-364, 2015.

Kahraman, C., Cebeci, U. & Ruan, D., Multi-attribute Comparison of Catering Service Companies Using Fuzzy AHP: The Case of Turkey, International Journal of Production Economics, 87(2), pp. 171-184, 2004.

Chou, Y-C., Sun, C-C. & Yen, H-Y., Evaluating the Criteria for Human Resource for Science and Technology (HRST) based on an Integrated Fuzzy AHP and Fuzzy DEMATEL Approach, Applied Soft Computing, 12(1), pp. 64-71, 2012.

Mishra, A.K., Deep, S. & Choudhary, A., Identification of Suitable Sites for Organic Farming Using AHP & GIS, The Egyptian Journal of Remote Sensing and Space Science, 18(2), pp. 181-193, 2015.

Sekhar, C., Patwardhan, M. & Vyas, V., A Delphi-AHP-TOPSIS Based Framework for the Prioritization of Intellectual Capital Indicators: A SMEs Perspective, Procedia – Social and Behavioral Sciences, 189, pp. 275-284, 2015.

Shaw, K., Shankar, R., Yadav, S.S. & Thakur, L.S., Supplier Selection Using Fuzzy AHP and Fuzzy Multi-Objective Linear Programming for Developing Low Carbon Supply Chain, Expert Systems with Applications, 39(9), pp. 8182-8192, 2012.

Guneri, A.F., Yucel, A. & Ayyildiz, G., An Integrated Fuzzy-LP Approach for a Supplier Selection Problem in Supply Chain Management, Expert Systems with Applications, 36(5), pp. 9223-9228, 2009.

Ahmadi-Javid, A., Seyedi, P. & Syam, S.S., A Survey of Healthcare Facility Location, Computers & Operations Research, 79, pp. 223-263, 2017.

Bojić, S., Đatkov, Đ., Brcanov, D., Georgijević, M. & Martinov, M., Location Allocation of Solid Biomass Power Plants: Case Study of Vojvodina, Renewable and Sustainable Energy Reviews, 26, pp. 769-775, 2013.

Saaty, T.L., A Scaling Method for Priorities in Hierarchical Structures, Journal of Mathematical Psychology, 15(3), pp. 234-281, 1977.

Saaty, T.L., The Analytic Hierarchy Process, New York: McGraw Hill International, 1980.

Choudhary, D. & Shankar, R., An STEEP-fuzzy AHP-TOPSIS Framework for Evaluation and Selection of Thermal Power Plant Location: A Case Study from India, Energy, 42(1), pp. 510-521, 2012.

DOI: http://dx.doi.org/10.5614%2Fj.eng.technol.sci.2018.50.5.8


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