Analysis of Light Rail Systems Utilizing in Urban Areas by Using an Integrated Entropy and EATWOS Methodologies

Year 2019, Volume: 10 Issue: 1, 254 - 267, 25.03.2019

Ömer Faruk Görçün

Abstract

Performance of urban transportation
systems is a vitally important matter in aspects of providing effective and
productive transportation service to the users who demand transport services. It can be seen that there are too many factors, which affect the
performance of a transportation system and the number of these factors and
their levels of effect can show the increase as a result of the development of
urban areas. Therefore, it may not be possible to take a right and proper
decision by public authorities depending on verbal judgments and personal
skills of decision-makers in the extremely variable environment. When it is
evaluated in this frame, evaluation of the effectivity, productivity and
performance of transportation systems, which operating in urban areas is a
multi-criteria decision-making problem. Therefore, in order to solve this
problem effectively, utilizing the multi-criteria decision-making (MCDM) methodologies
is necessary. In this study, as well as providing a systematic and structural
solution way, it is proposed a hybrid MCDM model, which can be applied by decision-makers
easily. This model is an integrated approach, which integrated two MCDM
methodologies such as entropy and EATWOS. While weights of factors are
determined by the entropy method. Afterward, effectivity, productivity, and
performance of decision alternatives, which analyzing are measured and they are
ranked according to their productivity scores. In order to examine the hybrid
model in the aspect of numerical and quantitative perspective, thirteen light
rail systems, which operating in European Countries were selected and
effectivity and productivity analysis for these lines by using this selected
hybrid model.

Keywords

Rail transportation systems, entropy, EATWOS, productivity analysis

Kentsel Lojistikte Kullanılan Hafif Raylı Sistem Hatlarının Entegre Entropi ve EATWOS Yöntemleri Kullanılarak Analizi

Abstract

Kentsel ulaşımda kullanılan sistemlerin performansı kent içinde ulaşım
hizmeti talep eden kullanıcılara etkin ve verimli ulaşım hizmeti sunulabilmesi
açısından son derece önem arz eden bir konudur. 
Bir ulaşım sisteminin performansına etki eden çok sayıda faktör
görülebilmekte, kentsel alanların gelişimi ile birlikte bu faktörlerin sayısı
ve etki düzeyi artış gösterebilmektedir. Dolayısıyla son derece değişken olan
bir çevrede yatırımda bulunan kamu otoritelerinin doğru ve en iyi kararı
vermeleri karar vericilerin deneyimlerine ve sözel yargılarına dayalı olarak
mümkün olmayabilmektedir. Bu çerçevede değerlendirildiği zaman kentsel alanlarda
kullanılan ulaşım sistemlerin etkinlik, verimlilik ve performanslarının
değerlendirilmesi ve gelecekteki ulaşım altyapılarına ilişkin kararların
alınması gerçekte çok kriterli bir karar verme problemidir. Dolayısıyla
problemin etkin bir biçimde çözümü çok kriterli karar verme yöntemlerinin
kullanılmasını zorunlu hale getirmektedir. Bu çalışmada karar verme probleminin
çözümü ile ilgili olarak sistematik ve yapısal bir çözüm yolu sağlamanın yanı
sıra, karar alıcılar tarafından kolayca uygulanacak hibrid bir çok kriterli
karar verme metodolojisi önerilmektedir. Bu model entropi ve EATWOS olarak
tanımlanan iki ÇKKV yönteminin entegre edilmesi ile oluşturulmuş bir model
olarak nitelendirilebilir. Entropi yöntemi ile faktör ağırlıkları
değerlendirilirken, EATWOS yöntemi ile değerlendirmeye alınan karar
noktalarının etkinlik, verimlilik ve performansları ölçülmüş ve en yüksek
değerden başlanarak karar noktaları sıralandırılmıştır. Modelin sayısal bir
perspektifte test edilmesi için araştırma alanı olarak en yüksek yolcu taşıma
kapasitesi ve hat uzunluğuna sahip olan ve Avrupa’da kullanılan 13 Tramvay ve
hafif raylı sistemleri belirlenmiş, seçilen hibrid modele göre söz konusu
hatların etkinlik ve verimlilik analizi gerçekleştirilmiştir.

Keywords

Raylı ulaşım sistemleri, entropi yöntemi, EATWOS, verimlilik analizi

References

• Referans1 Alfy, Z., Elhadary, R., & Elashry, A., (2010). Integrating GIS and MCDM to deal with landfill site selection. International Journal of Engineering & Technology IJET-IJENS, Cilt:10 Sayı: 06, 33-40.
• Referans2 Aydin, N., Celik, E., & Gumus A.T., (2015). A hierarchical customer satisfaction framework for evaluating rail transit systems of Istanbul. Transportation Research Part A: Policy and Practice, Cilt:7, 61-81. doi.org/10.1016/j.tra.2015.03.029
• Referans3 Bansal, A., Singh, R.K., Issar, S. & Varkey, J., (2014). Evaluation of vendors ranking by EATWOS approach. Journal of Advances in Management Research, Cilt: 11, Sayı: 3, 290-311. doi.org/10.1108/JAMR-02-2014-0009
• Referans4 Celik, E., Bilisik, O.N., Erdogan, M., Gumus A.T., & Baracli, H., (2015). An integrated novel interval type-2 fuzzy MCDM method to improve customer satisfaction in public transportation for Istanbul. Transportation Research Part E: Logistics and Transportation Review, Cilt: 58, 28-51. doi.org/10.1016/j.tre.2013.06.006
• Referans5 Farkas, A., (2009). Route/site selection of urban transportation facilities: an integrated GIS/MCDM approach. MEB 2009 – 7th International Conference on Management, Enterprise and Benchmarking, June 5‐6, 2009, Budapest, Hungary.
• Referans6 Fierek, S., & Zak, J., (2012). Planning of an integrated urban transportation system based on macro–simulation and MCDM/A methods. Procedia - Social and Behavioral Sciences, Cilt: 54, Sayı: 4, 567-579. doi.org/10.1016/j.sbspro.2012.09.774
• Referans7 Gerçek, H., Karpak, B., & Kılınçaslan, T., (2004). A multiple criteria approach for the evaluation of the rail transit networks in Istanbul. Transportation, Cilt: 31, Sayı: 2, 203–228. doi.org/10.1023/B:PORT.0000016572.41816.d2
• Referans8 Haijun, Z., (2005). Methodology to sequence the logistics centers based on entropy weighting and TOPSIS. Journal of Southeast University, Cilt: 35 Sayı: 6, 967-971. doi:10.1016/j.mcm.2010.07.023
• Referans9 Hamurcu, M., Alağaş, H.M., & Eren, T., (2017). Selection of rail system projects with analytic hierarchy process and goal programming. Sigma J Eng & Nat Sci, Cilt: 8, Sayı: 4, 291-302.
• Referans10 Kumar, N., Singh, A., Verma, A., & Sonal, T., (2016). Measuring efficiency of IPL players using EATWOS. International Journal of Advanced Production and Industrial Engineering, Cilt: 1, Sayı: 2, 13-16.
• Referans11 Li, Y., Zhao, L., & Suo, J., (2014). Comprehensive assessment on sustainable development of highway transportation capacity based on entropy weight and TOPSIS. Sustainability, 6(7):4685-4693. doi: 10.3390/su6074685
• Referans12 Nassereddine, M., & Eskandari, H., (2017). An integrated MCDM approach to evaluate public transportation systems in Tehran. Transportation Research Part A: Policy and Practice, Cilt: 106, 427-439. doi: 10.1016/j.tra.2017.10.013
• Referans13 Özbek, A., (2015a). Analysis of private pension companies in Turkey by EATWOS. European Journal of Business and Management, Cilt: 7, Sayı: 26, 31-43. ISSN 2222-1905
• Referans14 Özbek, A., (2015b). Efficiency analysis of the Turkish red crescent between 2012 and 2014. International Journal of Economics and Finance, Cilt: 7, Sayı:9, 322-334.
• Referans15 Özbek, A., (2015c). Efficiency analysis of non-governmental organizations based in Turkey. International Business Research, Cilt: 8, Sayı: 9, 95-104.
• Referans16 Özbek, A., (2016). Efficiency analysis of gold mining companies through financial statements. International Journal of Academic Research in Business and Social Sciences, Cilt: 6, Sayı: 10, 273-290.
• Referans17 Özbek, A., (2017a). Çok Ölçütlü Karar Verme Yöntemleriyle Hayırsever Kuruluşlarında Verimlilik Analizi Efficiency Analysis in Charity Organizations by Multiple Criteria Decision. Anadolu Üniversitesi Sosyal Bilimler Dergisi, Cilt: 18 - Sayı: 2, 99-114.
• Referans18 Özbek, A., (2017b). İlkokul öğretmenleri sağlik ve sosyal yardim sandiği'nin finansal performans analizi. Çankırı Karatekin Üniversitesi İİBF Dergisi, Cilt: 7, Sayı: 1, 1-31.
• Referans19 Pérez C. J., Carrillo, M.H., & Montoya-Torres, J.R. (2015). Multi-criteria approaches for urban passenger transport systems: a literature review. Annals of Operations Research, Cilt: 226, 69-87. doi:/10.1007/s10479-014-1681-8
• Referans20 Peters, M.L., Zelewski, S., & Bruns, A.S., (2012). Extended version of EATWOS concerning satisficing levels for input quantities. Pioneering supply chain, (Ed. Ringle C.M.), EUL Verlag, Hamburg.
• Referans21 Purahmad, A., Omranzadeh, B., & Mahdi, A., (2015). Evaluation and prioritization of rapid public transit systems in Tehran metropolis with TOPSIS and shannon entropy technique. Journal of Geography and Regional Development, Cilt: 12, Sayı: 23, 63 To 86.
• Referans22 Ranjan, R., Chatterjee, P., & Chakraborty, S., (2016) Performance evaluation of Indian Railway zones using DEMATEL and VIKOR methods. Benchmarking Int. J. Cilt: 23, Sayı: 1, 78–95. https://doi.org/10.1007/s40034-018-0113-8
• Referans23 Sari, I.U., Behret, H., & Kahraman C., (2012). Risk governance of urban rail systems using fuzzy AHP: the case of Istanbul … and Knowledge-Based Systems, International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, Cilt: 20, Sayı: supp01, 67-79. doi:/10.1142/S0218488512400053
• Referans24 Sivilevičius, H., & Maskeliūnaite, L., (2010). The criteria for identifying the quality of passengers' transportation by railway and their ranking using AHP method, Transport, Cilt:25 Sayı: 4, 368-381. doi.org/10.3846/transport.2010.46
• Referans25 Soni, V., Singh, S., & Banwet, D., (2016). Precise decisions in Indian energy sector by imprecise evaluation. International Journal of Energy Sector Management, Cilt: 10, Sayı:1, 111-118.
• Referans26 Wang, Y., Zhang, Z., & Sun H., (2018). Assessing customer satisfaction of urban rail transit network in Tianjin based on intuitionistic fuzzy group decision model. Discrete Dynamics in Nature and Society, Cilt: 2018, 1-11. doi: 10.1155/2018/4205136
• Referans27 Yongneng, X., (2009). Performance Evaluation for the Maintenance Systems TPM & RCM Applied in Nanjing Metro [J]. Urban Rapid Rail Transit, Cilt: 12, Sayı: 2, 81-89.
• Referans28 Zak, J., (2009). Multiple criteria evaluation and optimization of transportation systems. Journal of advanced transportation, Cilt:43 Sayı: 2, 91-94. https://doi.org/10.1002/atr.5670430202
• Referans29 Zhang, C., & Xu, L., (2009). Application of TOPSIS in Evaluating Transfer Efficiency at Urban Railway Passenger Station. International Conference on Transportation Engineering, 1866-1871.