Evaluating Potential Freight Villages in Istanbul Using Multi Criteria Decision Making Techniques
İstanbul Üniversitesi İşletme Fakültesi Sayısal Yöntemler Anabilim Dalı
İstanbul Üniversitesi İşletme Fakültesi Sayısal Yöntemler Anabilim Dalı
Evaluating freight villages and selecting one of them are complicated tasks due to the fact that various criteria or objectives must be considered in the decision making process. Also in many real world cases the criteria are not equally important for the logistic managers and government authorities. In this study, we proposed a freight village analysis model considering both Analytic Hierarchy Process (AHP) and PROMETHEE (preference ranking organization method for enrichment of evaluations) method. Subjective and objective opinions of logistic managers/experts turn into quantitative form with AHP. PROMETHEE technique is used for calculating the freight villages’ ratings. Apparently, freight village location selection is a multi-criteria problem that includes both quantitative and qualitative factors. It is necessary to make trade-off between these tangible and intangible factors while considering a suitable location. Accessibility, transport infrastructure, the value of freight villages (maritime connections, rail connections, road connections, and airport connections), distance from city center and total surface area are some of the key success factors of freight villages. The aim of this paper is to determine the appropriate freight village candidate providing the most satisfaction for the criteria identified in the supply chain management.
Jel Classification: C63
- Ertuğrul, İ and Karakaşoğlu, N 2008, 'Comparison of fuzzy AHP and fuzzy TOPSIS methods for facility location selection' International Journal of Advanced Manufacturing Technology, vol.39, no.7, pp.783-795.
- Bamyaci, M., (2008). “Modern Lojistik Yönetimi: Organize Lojistik Bölgeleri İçin Bir Yer Seçimi Modeli” Istanbul Universitesi, Fen Bilimleri Enstitusu, Doktora Tezi, In Turkish.
- Janic, M. and Reggiani, A.,(2002). An Application of the Multiple Criteria Decision Making (MCDM) Analysis to the Selection of a New Hub Airport, EJTIR, 2, no. 2, pp. 113 – 141.
- Jaržemskis, A., (2007). Research On Public Logistics Centre As Tool For Cooperation, Transport ,Vol XXII, No 1, 50–54.
- Ballis, A. and Mavrotas, G., (2007), Freight village design using the multicriteria method PROMETHEE.Operational Research. An International Journal., Vol. 7, No. 2, pp. 213-232.
- Lindholm, M. and Behrends, S., (2012). Challenges in urban freight transport planning – a review in the Baltic Sea Region, Journal of Transport Geography 22, 129–136.
- Cerreno, A. L. C., Shin, H., S., Wieder, A.S. and Theofanis, S., (2008). Feasibility of Freight Villages in the New York Metropolitan Transportation Council (NYMTC) Region, Center for Advanced Infrastructure and Transportation Freight and Maritime Program, 1-23.
- Yanga, L., Jib, X.,Gaoa, Z. and Li, K., (2007). Logistics distribution centers location problem and algorithm under fuzzy environment, Journal of Computational and Applied Mathematics 208, 303 – 315.
- Awasthi, A., Chauhan, S.S. and Goyal, S.K., (2011). A multi-criteria decision making approach for location planning for urban distribution centers under uncertainty, Mathematical and Computer Modelling, 53, 98–109.
- Li, Y., Liu, X. and Chen, Y., (2011). Selection of logistics center location using Axiomatic Fuzzy Set and TOPSIS methodology in logistics management, Expert Systems with Applications 38, 7901–7908.
- Taniguchi, E., Noritake, M., , Yamada, T. and Izumitani, T., (1999). Optimal size and location planning of public logistics terminals, Transportation Research Part E 35, 207-222.
- Sirikijpanichkul, A. and Ferreira, L., (2006). Solving the Conflicts in Intermodal Freight Hub Location Decisions, BEE Postgraduate Infrastructure Theme Conference, 26th September 2006, Gardens Point Campus, Queensland University of Technology.
- Liberatore, M.J., Nydick, R.L., (1997). Group Decision Making In Higher Education Using The Analytic Hierarchy Process, Research In Higher Education, Vol. 38, No. 5.
- Yoo, K.E, Choi, Y.C.,(2006). Analytic Hierarchy Process Approach For Identifying Relative Importance Of Factors To Improve Passenger Security Checks At Airports, Journal of Air Transport Management 12, 135–142.
- Dagdeviren, M., Yavuz, S., Kilinc, N., 2009. Weapon selection using the AHP and TOPSIS methods under fuzzy environment, Expert Systems with Applications, 36, 8143-8151.
- Saaty, T.L., (1990). How To Make Decision: The Analytic Hierarchy Process, European Journal of Operational Research, North_Holland, 48, 9-26.
- Saaty, T. L.,(2008). Decision Making With The Analytic Hierarchy Process. Int. J. Services Sciences, 1 (1), 83.
- Saaty, T. L., Vargas Luis L., (2001). Models, Methods, Concepts & Applications of The Analytic Hierarchy Process. International Series in Operations Research & Management Science, Kluwer Academic Publishers.
- Lee, S., Kim, W., Kim, Y.M., Oh, K.J., 2012.Using AHP to determine intangible priority factors for technology transfer adoption. Expert Systems with Applications, 39, 6388-6395.
- J.P. Brans (1982). "L’ingénierie de la décision: élaboration d’instruments d’aide à la décision. La méthode PROMETHEE.". Presses de l’Université Laval.
- J.P. Brans and P. Vincke (1985). "A preference ranking organisation method: The PROMETHEE method for MCDM". Management Science.
- De Brucker, K., Verbeke, A., Macharis, C., (2004), The applicability of multicriteria-analysis to the evaluation of intelligent transport systems (ITS). Research in Transportation Economics, 8, 151-179.
- Behzadian Majid, R.B. Kazemzadeh, A. Albadvi, M. Aghdasi, (2010), PROMETHEE: A comprehensive literature review on methodologies and applications, European Journal of Operational Research, 200, 198–215.
- M. Shakhsi-Niaei, S.A. Torabi, S.H. Iranmanesh, (2011), A comprehensive framework for project selection problem under uncertainty and real-world constraints, Computers & Industrial Engineering 61, 226–237.
- Turcksina Laurence, Annalia Bernardinia, Cathy Macharisa, (2011), A combined AHP-PROMETHEE approach for selecting the most appropriate policy scenario to stimulate a clean vehicle fleet, Procedia Social and Behavioral Sciences, 20, 954–965.
- Macharis Cathy, Johan Springael, Klaas De Brucker, Alain Verbeke, (2004), PROMETHEE and AHP: The design of operational synergies in multicriteria analysis. Strengthening PROMETHEE with ideas of AHP, European Journal of Operational Research, 153, 307–317.
- Brans, J.P.., Mareschal, B. and Vincke, P. (1986) 'How To Select And How To Rank Projects : The PROMETHEE Method for MCDM', EJOR, 24, pp.228-238.
- Li Wei-xianga, Li Bang-yi, (2010), An extension of the Promethee II method based on generalized fuzzy numbers, Expert Systems with Applications, 37, 5314–5319.
- Hyde, K., Maier, H. R., & Colby, C. (2003). Incorporating uncertainty in the PROMETHEE MCDA method. Journal of Multi-Criteria Decision Analysis, 12, 245–259.
Jung, H., Jeon, J., & Choi, H. (2021). Important Factors in the Development of Biopharmaceutical Logistics Centers. The Asian Journal of Shipping and Logistics. doi:10.1016/j.ajsl.2021.07.003
Kabassi, K. (2021). Comparing Multi-Criteria Decision Making Models for Evaluating Environmental Education Programs. Sustainability, 13(20), 11220. doi:10.3390/su132011220
Alidrisi, H. (2021). DEA-Based PROMETHEE II Distribution-Center Productivity Model: Evaluation and Location Strategies Formulation. Applied Sciences, 11(20), 9567. doi:10.3390/app11209567
Kabassi, K., & Martinis, A. (2021). Sensitivity Analysis of PROMETHEE II for the Evaluation of Environmental Websites. Applied Sciences, 11(19), 9215. doi:10.3390/app11199215
Komchornrit, K. (2021). Location Selection of Logistics Center: A Case Study of Greater Mekong Subregion Economic Corridors in Northeastern Thailand. ABAC Journal, 41(2), 137-155.
Keleş, N., Pekkaya, M. (2021). Lojistik Köy Yer Seçiminde Dikkate Alınan Değişkenlerin Kıyaslama Yaklaşımı İle Belirlenmesi. Bartın Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 12(23), article in press. DOI: 10.47129/bartiniibf.840819
Liang, F., Verhoeven, K., Brunelli, M., & Rezaei, J. (2021). Inland terminal location selection using the multi-stakeholder best-worst method. International Journal of Logistics Research and Applications, 1-23.
MakaleBattal, T. (2020). Understanding the logistics centre location decision: what are the main decision criteria and evaluation methods?. International Journal of Logistics Economics and Globalisation, 8(2), 154-192. https://dx.doi.org/10.1504/IJLEG.2020.1082
Ulutaş, A., Karakuş, C. B., & Topal, A. (2020). Location selection for logistics center with fuzzy SWARA and cocoso methods. Journal of Intelligent & Fuzzy Systems, (Preprint), 1-17. http://doi.org/10.3233/jifs-191400
Sopha, B. M., Sakti, S., Prasetia, A. C. G., Dwiansarinopa, M. W., & Cullinane, K. (2020). Simulating long-term performance of regional distribution centers in archipelagic logistics systems. Maritime Economics & Logistics, 1-29.
Komchornrit, K., & Weerawat, W. (2020). Modeling Framework of Hybrid Method for Site Selection of Dry Port: A Case Study in Southern Region of Thailand. Applied Science and Engineering Progress, 13(3), 233-245.
MakaleDemirkıran, Y., Öztürkoğlu, Ö. (2020). Türkiye’deki Bölgelerin Lojistik Köy Kurulması Açısından Potansiyelinin PROMETHEE II Yöntemi ile İncelenmesi Yaşar Üniversitesi E-Dergisi, 15 (58), 347-367. DOI: 10.19168/jyasar.616496
Aljohani, K., & Thompson, R. G. (2020). A multi-criteria spatial evaluation framework to optimise the siting of freight consolidation facilities in inner-city areas. Transportation Research Part A: Policy and Practice, 138, 51-69.
Novoselov, O. G., Timirov, E. V., Akhmadieva, A. S., & Fargatovna, M. A. (2020). Determination of Optimal Cost and Environmental Evaluation of Highways Using a Mathematical Model. Procedia Environmental Science, Engineering and Management, 7(4), 487-495.
Uyanik, C., Tuzkaya, G., Kalender, Z. , T., & Oguztimur, S. (2020). An integrated DEMATEL–IF-TOPSIS methodology for logistics centers’ location selection problem: an application for Istanbul Metropolitan area. Transport, 1-9.
Kumar, A., & Anbanandam, R. (2019). Location selection of multimodal freight terminal under STEEP sustainability. Research in Transportation Business & Management, 33, 100434. doi: 10.1016/j.rtbm.2020.100434
Yao, Y., Liu, P., Hong, Y., Liang, Z., Wang, R., Guan, Q., & Chen, J. (2019). Fine‐scale intra‐and inter‐city commercial store site recommendations using knowledge transfer. Transactions in GIS, 23(5), 1029-1047.
Ighravwe, D. (2019). Techno-economic assessment of small-scale renewable energy storage technologies. Decision Science Letters, 8(3), 363-372.
MakaleKartal, C. (2019). MOORA Metodu ile Portföy Yönetimi Geleneksel Yöntemlere ve Şans Faktörüne Dayalı Portföylerle Bir Karşılaştırma Uygulaması. Maliye ve Finans Yazıları, (111), 299-318.
MakaleUyanik, C., Tuzkaya, G., & Oğuztimur, S. (2018). A Literature Survey on Logistics Centers' Location Selection Problem. Sigma: Journal of Engineering & Natural Sciences/Mühendislik ve Fen Bilimleri Dergisi, 36(1), 141-160.
MakaleKim, S., Park, S., Woo, S., & Lee, S. (2017). Development and Analysis of the Interchange Centrality Evaluation Index Using Network Analysis. Journal of Korean Society of Transportation, 35(6), 525-544.
MakaleKomchornrit, K. (2017). The Selection of Dry Port Location by a Hybrid CFA-MACBETH-PROMETHEE Method: A Case Study of Southern Thailand. The Asian Journal of Shipping and Logistics, 33(3), 141–153. doi. 10.1016/j.ajsl.2017.09.004
Pham, T. Y., Ma, H. M., & Yeo, G. T. (2017). Application of Fuzzy Delphi TOPSIS to locate logistics centers in Vietnam: The Logisticians’ perspective. The Asian Journal of Shipping and Logistics, 33(4), 211-219.
Peker, I., Baki, B., Tanyas, M., & Murat Ar, I. (2016). Logistics center site selection by ANP/BOCR analysis: A case study of Turkey [JB]. Journal of Intelligent & Fuzzy Systems, 30(4), 2383–2396. doi. 10.3233/IFS-152007
Özceylan, E., Erbaş, M., Tolon, M., Kabak, M., & Durğut, T. (2016). Evaluation of freight villages: A GIS-based multi-criteria decision analysis. Computers in Industry, 76, 38-52. doi: 10.1016/j.compind.2015.12.003