Facility Location Selection using Preference Programming
This paper presents preference programming technique based multiple criteria decision making analysis for selecting a facility location for a new organization or expansion of an existing facility which is of vital importance for a decision support system and strategic planning process. The implementation of decision support systems is considered crucial to sustain competitive advantage and profitability persistence in turbulent environment. As an effective strategic management and decision making is necessary, multiple criteria decision making analysis supports the decision makers to formulate and implement the right strategy. The investment cost associated with acquiring the property and facility construction makes the facility location selection problem a long-term strategic investment decision, which rationalize the best location selection which results in higher economic benefits through increased productivity and optimal distribution network. Selecting the proper facility location from a given set of alternatives is a difficult task, as many potential qualitative and quantitative multiple conflicting criteria are to be considered. This paper solves a facility location selection problem using preference programming, which is an effective multiple criteria decision making analysis tool applied to deal with complex decision problems in the operational research environment. The ranking results of preference programming are compared with WSM, TOPSIS and VIKOR methods.
[1] Chou, S.Y., Chang, Y.H. and Shen, C.Y. (2008), “A fuzzy simple additive weighting system under group decision-making for facility location selection with objective/subjective attributes”, European Journal of Operational Research, Vol. 189 No. 1, pp. 132-145.
[2] Choudhary, D. and Shankar, R. (2012), “A STEEP-fuzzy AHP-TOPSIS framework for evaluation and selection of thermal power plant location: a case study from India”, Energy, Vol. 42 No. 1, pp. 510-521.
[3] Chu, T.C. (2002), “Facility location selection using fuzzy TOPSIS under group decisions”, International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, Vol. 10 No. 6, pp. 687-701.
[4] Yang, J., Lee, H. (1997). An AHP decision model for facility location selection. Facilities, Vol. 15 No. 9/10, pp. 241-254. https://doi.org/10.1108/02632779710178785.
[5] Dag, S., Onder, E. (2013). Decision-making for facility location using vikor method. Journal of International Scientific Publications: Economy & Business, cilt.7, ss.308-33.
[6] Yaslioglu, M.M., Onder, E. (2016). Solving Facility Location Problem for a Plastic Goods Manufacturing Company in Turkey Using AHP and TOPSIS Methods.Yönetim Bilimleri Dergisi / Journal of Administrative Sciences, Cilt / Volume: 14, Sayı / N: 28, ss. / pp.: 223-249.
[7] Vahdani, B., Mousavi, S., Tavakkoli-Moghaddam, R. (2013). Plant Location Selection by Using a Three-Step Methodology: Delphi-AHP-VIKOR. World Academy of Science, Engineering and Technology, Open Science Index 78, International Journal of Industrial and Manufacturing Engineering, 7(6), 1289 - 1292.
[8] Koç, E., Burhan, H. (2016). Analytic Network Process in Location Selection and Its Application to a Real Life Problem. World Academy of Science, Engineering and Technology, Open Science Index 111, International Journal of Computer and Information Engineering, 10(3), 507 - 512.
[9] Zaralı, F., Yazgan, H. (2016). Solution of Logistics Center Selection Problem Using the Axiomatic Design Method. World Academy of Science, Engineering and Technology, Open Science Index 111, International Journal of Computer and Information Engineering, 10(3), 547 - 553.
[10] Cinar, N. (2009). A Decision Support Model for Bank Branch Location Selection. World Academy of Science, Engineering and Technology, Open Science Index 36, International Journal of Mathematical and Computational Sciences, 3(12), 1092 - 1097.
[11] Athawale, V. M., Chatterjee, P., Chakraborty, S. (2012). Decision making for facility location selection using PROMETHEE II method. International Journal of Industrial and Systems Engineering (IJISE), Vol. 11, No. 1/2.
[12] Ankita, R., De, A., Dan, P. Kr. (2015). Facility location selection using complete and partial ranking MCDM methods. International Journal of Industrial and Systems Engineering, Vol. 19, No. 2.
[13] Mousavi, S.M., Tavakkoli-Moghaddam, R., Heydar, M. et al. Multi-Criteria Decision Making for Plant Location Selection: An Integrated Delphi–AHP–PROMETHEE Methodology. Arab J Sci Eng 38, 1255–1268 (2013). https://doi.org/10.1007/s13369-012-0361-8.
[14] Sennaroglu, B., Celebi, G. V. (2018). A military airport location selection by AHP integrated PROMETHEE and VIKOR methods.Transportation Research Part D: Transport and Environment, Volume 59, 160-173.
[15] Brans, J., Ph. Vincke. (1985). A Preference Ranking Organisation Method: (The PROMETHEE Method for Multiple Criteria Decision-Making). Management Science, 31(6), 647-656. Retrieved June 28, 2021, from http://www.jstor.org/stable/2631441.
[16] Brans, J.P., Vincke, Ph., Mareschal, B., (1986). How to select and how to rank projects: the PROMETHEE method. European Journal of Operational Research, 24, 228-238.
[17] Brans, J.P., Macharis, C., Kunsch, P.L., Chevalier, A., Schwaninger, M., (1998). Combining multicriteria decision aid and system dynamics for the control of socio-economic processes. An iterative real-time procedure. European Journal of Operational Research 109, 428-441.
[18] Brans, J.P. and Mareschal, B., (2005). Chapter 5: PROMETHEE methods, 164-195.
[19] Rao, R. V. (2007). Decision Making in the Manufacturing Environment. Using Graph Theory and Fuzzy Multiple Attribute Decision Making Methods. ISBN 978-1-84628-819-7.
[20] Ardil, C., Bilgen, S. (2017) Online Performance Tracking. SocioEconomic Challenges, 1(3), 58-72. ISSN (print) – 2520-6621.
[21] Hwang, C.L.; Yoon, K. (1981). Multiple Attribute Decision Making: Methods and Applications. New York: Springer-Verlag.
[22] Opricovic, S., Tzeng, G-H., (2004). Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS. European Journal of Operational Research,vol. 156(2), 445-455.
[23] Opricovic, S., Tzeng, G.-H. (2007). Extended VIKOR method in comparison with outranking methods. European Journal of Operational Research, vol. 178(2), 514-529.
[24] Ardil, C. (2018) Multidimensional Performance Tracking. International Journal of Computer and Systems Engineering, Vol:12, No:5,320-349
[25] Ardil, C. (2018) Multidimensional Compromise Optimization for Development Ranking of the Gulf Cooperation Council Countries and Turkey. International Journal of Mathematical and Computational
Sciences Vol:12, No:6, 131-138.
[26] Ardil, C. (2018) Multidimensional Compromise Programming Evaluation of Digital Commerce Websites. International Journal of Computer and Information Engineering Vol:12, No:7, 556-563.
[27] Ardil, C. (2018) Multicriteria Decision Analysis for Development Ranking of Balkan Countries. International Journal of Computer and
Information Engineering Vol:12, No:12, 1118-1125.
[28] Ardil, C. (2019) Scholar Index for Research Performance Evaluation Using Multiple Criteria Decision Making Analysis. International Journal of Educational and Pedagogical Sciences, Vol:13, No:2, 93-105.
[29] Ardil, C. (2019) Military Fighter Aircraft Selection Using Multiplicative Multiple Criteria Decision Making Analysis Method. International Journal of Mathematical and Computational Sciences, 13(9), 184 - 193.
[30] Ardil, C. (2019) Fighter Aircraft Selection Using Technique for Order Preference by Similarity to Ideal Solution with Multiple Criteria Decision Making Analysis. International Journal of Transport and Vehicle Engineering, Vol:13, No:10, 649-657.
[31] Ardil, C., Pashaev, A. M., Sadiqov, R.A., Abdullayev, P. (2019) Multiple Criteria Decision Making Analysis for Selecting and Evaluating Fighter Aircraft. International Journal of Transport and Vehicle Engineering, Vol:13, No:11, 683-694.
[32] Ardil, C. (2019) Aircraft Selection Using Multiple Criteria Decision Making Analysis Method with Different Data Normalization Techniques. International Journal of Industrial and Systems Engineering, Vol:13, No:12, 744-756.
[1] Chou, S.Y., Chang, Y.H. and Shen, C.Y. (2008), “A fuzzy simple additive weighting system under group decision-making for facility location selection with objective/subjective attributes”, European Journal of Operational Research, Vol. 189 No. 1, pp. 132-145.
[2] Choudhary, D. and Shankar, R. (2012), “A STEEP-fuzzy AHP-TOPSIS framework for evaluation and selection of thermal power plant location: a case study from India”, Energy, Vol. 42 No. 1, pp. 510-521.
[3] Chu, T.C. (2002), “Facility location selection using fuzzy TOPSIS under group decisions”, International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, Vol. 10 No. 6, pp. 687-701.
[4] Yang, J., Lee, H. (1997). An AHP decision model for facility location selection. Facilities, Vol. 15 No. 9/10, pp. 241-254. https://doi.org/10.1108/02632779710178785.
[5] Dag, S., Onder, E. (2013). Decision-making for facility location using vikor method. Journal of International Scientific Publications: Economy & Business, cilt.7, ss.308-33.
[6] Yaslioglu, M.M., Onder, E. (2016). Solving Facility Location Problem for a Plastic Goods Manufacturing Company in Turkey Using AHP and TOPSIS Methods.Yönetim Bilimleri Dergisi / Journal of Administrative Sciences, Cilt / Volume: 14, Sayı / N: 28, ss. / pp.: 223-249.
[7] Vahdani, B., Mousavi, S., Tavakkoli-Moghaddam, R. (2013). Plant Location Selection by Using a Three-Step Methodology: Delphi-AHP-VIKOR. World Academy of Science, Engineering and Technology, Open Science Index 78, International Journal of Industrial and Manufacturing Engineering, 7(6), 1289 - 1292.
[8] Koç, E., Burhan, H. (2016). Analytic Network Process in Location Selection and Its Application to a Real Life Problem. World Academy of Science, Engineering and Technology, Open Science Index 111, International Journal of Computer and Information Engineering, 10(3), 507 - 512.
[9] Zaralı, F., Yazgan, H. (2016). Solution of Logistics Center Selection Problem Using the Axiomatic Design Method. World Academy of Science, Engineering and Technology, Open Science Index 111, International Journal of Computer and Information Engineering, 10(3), 547 - 553.
[10] Cinar, N. (2009). A Decision Support Model for Bank Branch Location Selection. World Academy of Science, Engineering and Technology, Open Science Index 36, International Journal of Mathematical and Computational Sciences, 3(12), 1092 - 1097.
[11] Athawale, V. M., Chatterjee, P., Chakraborty, S. (2012). Decision making for facility location selection using PROMETHEE II method. International Journal of Industrial and Systems Engineering (IJISE), Vol. 11, No. 1/2.
[12] Ankita, R., De, A., Dan, P. Kr. (2015). Facility location selection using complete and partial ranking MCDM methods. International Journal of Industrial and Systems Engineering, Vol. 19, No. 2.
[13] Mousavi, S.M., Tavakkoli-Moghaddam, R., Heydar, M. et al. Multi-Criteria Decision Making for Plant Location Selection: An Integrated Delphi–AHP–PROMETHEE Methodology. Arab J Sci Eng 38, 1255–1268 (2013). https://doi.org/10.1007/s13369-012-0361-8.
[14] Sennaroglu, B., Celebi, G. V. (2018). A military airport location selection by AHP integrated PROMETHEE and VIKOR methods.Transportation Research Part D: Transport and Environment, Volume 59, 160-173.
[15] Brans, J., Ph. Vincke. (1985). A Preference Ranking Organisation Method: (The PROMETHEE Method for Multiple Criteria Decision-Making). Management Science, 31(6), 647-656. Retrieved June 28, 2021, from http://www.jstor.org/stable/2631441.
[16] Brans, J.P., Vincke, Ph., Mareschal, B., (1986). How to select and how to rank projects: the PROMETHEE method. European Journal of Operational Research, 24, 228-238.
[17] Brans, J.P., Macharis, C., Kunsch, P.L., Chevalier, A., Schwaninger, M., (1998). Combining multicriteria decision aid and system dynamics for the control of socio-economic processes. An iterative real-time procedure. European Journal of Operational Research 109, 428-441.
[18] Brans, J.P. and Mareschal, B., (2005). Chapter 5: PROMETHEE methods, 164-195.
[19] Rao, R. V. (2007). Decision Making in the Manufacturing Environment. Using Graph Theory and Fuzzy Multiple Attribute Decision Making Methods. ISBN 978-1-84628-819-7.
[20] Ardil, C., Bilgen, S. (2017) Online Performance Tracking. SocioEconomic Challenges, 1(3), 58-72. ISSN (print) – 2520-6621.
[21] Hwang, C.L.; Yoon, K. (1981). Multiple Attribute Decision Making: Methods and Applications. New York: Springer-Verlag.
[22] Opricovic, S., Tzeng, G-H., (2004). Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS. European Journal of Operational Research,vol. 156(2), 445-455.
[23] Opricovic, S., Tzeng, G.-H. (2007). Extended VIKOR method in comparison with outranking methods. European Journal of Operational Research, vol. 178(2), 514-529.
[24] Ardil, C. (2018) Multidimensional Performance Tracking. International Journal of Computer and Systems Engineering, Vol:12, No:5,320-349
[25] Ardil, C. (2018) Multidimensional Compromise Optimization for Development Ranking of the Gulf Cooperation Council Countries and Turkey. International Journal of Mathematical and Computational
Sciences Vol:12, No:6, 131-138.
[26] Ardil, C. (2018) Multidimensional Compromise Programming Evaluation of Digital Commerce Websites. International Journal of Computer and Information Engineering Vol:12, No:7, 556-563.
[27] Ardil, C. (2018) Multicriteria Decision Analysis for Development Ranking of Balkan Countries. International Journal of Computer and
Information Engineering Vol:12, No:12, 1118-1125.
[28] Ardil, C. (2019) Scholar Index for Research Performance Evaluation Using Multiple Criteria Decision Making Analysis. International Journal of Educational and Pedagogical Sciences, Vol:13, No:2, 93-105.
[29] Ardil, C. (2019) Military Fighter Aircraft Selection Using Multiplicative Multiple Criteria Decision Making Analysis Method. International Journal of Mathematical and Computational Sciences, 13(9), 184 - 193.
[30] Ardil, C. (2019) Fighter Aircraft Selection Using Technique for Order Preference by Similarity to Ideal Solution with Multiple Criteria Decision Making Analysis. International Journal of Transport and Vehicle Engineering, Vol:13, No:10, 649-657.
[31] Ardil, C., Pashaev, A. M., Sadiqov, R.A., Abdullayev, P. (2019) Multiple Criteria Decision Making Analysis for Selecting and Evaluating Fighter Aircraft. International Journal of Transport and Vehicle Engineering, Vol:13, No:11, 683-694.
[32] Ardil, C. (2019) Aircraft Selection Using Multiple Criteria Decision Making Analysis Method with Different Data Normalization Techniques. International Journal of Industrial and Systems Engineering, Vol:13, No:12, 744-756.
@article{"International Journal of Mechanical, Industrial and Aerospace Sciences:80486", author = "C. Ardil", title = "Facility Location Selection using Preference Programming", abstract = "This paper presents preference programming technique based multiple criteria decision making analysis for selecting a facility location for a new organization or expansion of an existing facility which is of vital importance for a decision support system and strategic planning process. The implementation of decision support systems is considered crucial to sustain competitive advantage and profitability persistence in turbulent environment. As an effective strategic management and decision making is necessary, multiple criteria decision making analysis supports the decision makers to formulate and implement the right strategy. The investment cost associated with acquiring the property and facility construction makes the facility location selection problem a long-term strategic investment decision, which rationalize the best location selection which results in higher economic benefits through increased productivity and optimal distribution network. Selecting the proper facility location from a given set of alternatives is a difficult task, as many potential qualitative and quantitative multiple conflicting criteria are to be considered. This paper solves a facility location selection problem using preference programming, which is an effective multiple criteria decision making analysis tool applied to deal with complex decision problems in the operational research environment. The ranking results of preference programming are compared with WSM, TOPSIS and VIKOR methods.", keywords = "Facility Location Selection, Multiple Criteria Decision Making, Multiple Criteria Decision Making Analysis, Preference Programming, Location Selection, WSM, TOPSIS, VIKOR", volume = "14", number = "1", pages = "41-12", }
