Akıllı kentsel lojistik çözümlerinin bulanık ÇKKV yöntemleri ile değerlendirilmesi

Yıl 2019, Cilt: 25 Sayı: 9, 1033 - 1040, 31.12.2019

Gülçin Büyüközkan , Esin Mukul

Öz

Lojistiğin bir alt dalı olarak incelenmeye başlanan "Kentsel Lojistik", genel lojistikte olduğu gibi dağıtım ve ulaşımın planlanmasını, yönetilmesini, etkin bir lojistik sisteminin sağlanmasını, çevrenin korunmasını, trafiğin azaltılmasını, lojistikte güvenliği ve enerji tasarrufunu amaçlamaktadır. Hızla artan nüfus ve kırsal alanlardan kentsel alanlara olan göç, şehirdeki lojistik problemlerinin yaşanmasındaki başlıca sebepler arasındadır. Akıllı şehir yaklaşımı, bilgi teknolojileri ile bu problemleri çözmek için önemli bir potansiyele sahiptir. Lojistik hizmetlerinde artan talebin daha etkin, güvenli ve çevreci bir şekilde karşılanması için bilgi teknolojilerini baz alan tam adaptif trafik yönetim sistemi, güvenlik ve acil durum yönetim sistemi, elektronik denetleme sistemi gibi “Akıllı kentsel lojistik çözümleri” sunulmaktadır. Bu çalışmada, birçok bileşeni bünyesinde barındıran akıllı kentsel lojistik çözümleri, Çok Kriterli Karar Verme (ÇKKV) problemi olarak ele alınmaktadır. Bu problemin karmaşık yapısı ve bilginin yetersiz olduğu göz önünde bulundurularak karar verme yaklaşımı bulanık mantık ile desteklenmektedir. Bu kapsamda, İstanbul’da akıllı kentsel lojistik çözümleri literatür taraması ve uzman görüşleri ile modellenmekte, analiz edilmekte ve sonuçlar Kalite Fonksiyon Göçerimi yaklaşımının Kalite Evi matrisi ve bir bulanık ÇKKV tekniği kullanılarak elde edilmektedir.

Anahtar Kelimeler

Akıllı kentsel lojistik, Akıllı kentsel lojistik çözümleri, Bulanık ÇKKV, Kalite Evi

Evaluation of smart city logistics solutions with fuzzy MCDM methods

Öz

City logistics, which started to examine as a subdivision of logistics, aims the planning and management of transportation, efficiency, protection of the environment, reduction of traffic, security, and energy-saving. Rapidly growing population and migration from rural to urban areas have an important place in many of the problems of cities. A smart city is an approach that has a significant potential to solve urban logistics problems with information technologies. "Smart city logistics solutions" such as full adaptive traffic management system, security, and emergency systems, electronic detection system, etc. present based on information technologies to meet the increasing demand for logistics services more efficiently, safely and environmentally. In this study, the evaluation of smart city logistics solutions that contain many components is considered as a multi-criteria decision-making (MCDM) problem. Given the complex nature of this problem and insufficient knowledge, the decision-making approach is supported by fuzzy logic. In this context, the smart city logistics solutions in Istanbul determined by literature review and expert opinions are modeled, analyzed, and the results are interpreted by using the House of Quality matrix of Quality Function Deployment (QFD) approach with fuzzy MCDM methods.

Anahtar Kelimeler

Fuzzy MCDM, House of Quality, Smart city logistics, Smart city logistics solutions

Kaynakça

• Taniguchi E, Thompson RG, Yamada T. “Modelling city logistics”. International Conference on City Logistics, 1st, Cairns, Queensland, Australia, 1999.
• Nowicka K. “Smart city logistics on cloud computing model”. Procedia-Social and Behavioral Sciences, 151, 266-281, 2014.
• BVRLA Policy Paper. “Intelligent Mobility”. 2016.
• UNECE. “Intelligent Transport Systems (ITS) for sustainable mobility”. 2012.
• Kirch M, Poenicke O, Richter K. “RFID in Logistics and Production-Applications, Research and Visions for Smart Logistics Zones”. Procedia Engineering, 178, 526-533, 2017.
• Hwang CL, Yoon K. Methods for Multiple Attribute Decision Making. In Multiple Attribute Decision Making. Springer, Berlin, Heidelberg, 58-191, 1981.
• Roszkowska, E., Kacprzak, D. “The fuzzy SAW and fuzzy TOPSIS procedures based on ordered fuzzy numbers”. Information Sciences, 369, 564-584, 2016.
• Tufan H. Akilli Ulaşim Sistemleri Uygulamalari ve Türkiye için bir AUS Mimarisi Önerisi. Ulaştırma ve Haberleşme Uzmanlığı Tezi, TC Ulaştırma Denizcilik ve Haberleşme Bakanlığı. 2014.
• T. C. Ministry of Transport, Maritime Affairs and Communications. “National Intelligent Transportation Systems Strategy Document and Action Plan: 2014-2023”, 2014.
• Zanelli P. “Intelligent Mobility., CATAPULT Transport Systems Report, 2016.
• Viechnicki P, Khuperkar A, Fishman T, Eggers W. “Smart mobility: Reducing congestion and fostering faster, greener, and cheaper transportation options”. Deloitte Smart Mobility Research Report. 2015.
• Buyukozkan G, Göçer F. “Prioritizing the Strategies to Enhance Smart City Logistics by Intuitionistic Fuzzy CODAS”. Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and Technology (EUSFLAT 2019), Prague, Czechia, 09-13 September 2019.
• Korczak J, Kijewska K. “Smart Logistics in the development of Smart Cities”. Transportation Research Procedia, 39, 201-211, 2019.
• Taniguchi E, Thompson RG. “Future developments modelling information and. Urban Logistics: Management”. Policy and Innovation in a Rapidly Changing Environment, 336, 2018.
• Stoller CW, Wan W. “Smart City Logistics-Ein Besuch in Schanghai”. Internationales Verkehrswesen, 70(4), 2018.
• Kaźmierczak J, Hilarowicz A, Wolny M. “Introduction to the research project “smart city: a holistic approach”, International Multidisciplinary Scientific Conference on Social Sciences and Arts (SGEM), Albena, Bulgaria, 26 August-01 September 2018.
• Bachanek KH. “Development of IT Services in Urban Space–Smart City Logistics”. European Journal of Service Management, 28, 27, 2018.
• Gruler AC. Simheuristics to support efficient and sustainable freight transportation in smart city logistics, PhD Thesis, University of Catalonia, 2018.
• Eitzen H, Lopez-Pires F, Baran B, Sandoya F, Chicaiza JL. “A multi-objective two-echelon vehicle routing problem. An urban goods movement approach for smart city logistics”. XLIII Latin American Computer Conference (CLEI), 1-10, Cordoba, Argentina, 04-08 September 2017.
• Shuai L, Hong-chun W. “Discussion on the problems and countermeasures of smart city logistics system”. IEEE Control and Decision Conference (CCDC), Chongqing, China, 28-30 May 2017.
• Bektaş T, Crainic TG, Van Woensel T. “From managing urban freight to smart city logistics networks”. Network Design and Optimization for Smart Cities, 143-188, 2017.
• Melo S, Macedo J, Baptista P. “Guiding cities to pursue a smart mobility paradigm: An example from vehicle routing guidance and its traffic and operational effects”. Research in transportation economics, 65, 24-33, 2017.
• Kauf S. “City logistics–A Strategic Element of Sustainable Urban Development”. Transportation Research Procedia, 16, 158-164, 2016.
• Nocerino R, Colorni A, Lia F, Luè A. “E-bikes and E-scooters for smart logistics: environmental and economic sustainability in pro-E-bike Italian pilots”. Transportation Research Procedia, 14, 2362-2371, 2016.
• Nathanail E, Gogas M, Adamos G. “Smart interconnections of interurban and urban freight transport towards achieving sustainable city logistics”. Transportation Research Procedia, 14, 983-992, 2016.
• Baudel T, Dablanc L, Alguiar-Melgarejo P, Ashton J. “Optimizing urban freight deliveries: from designing and testing a prototype system to addressing real life challenges”. Transportation Research Procedia, 12, 170-180, 2016.
• Guerlain C, Cortina S, Renault S. “Towards a collaborative Geographical Information System to support collective decision making for urban logistics initiative”. Transportation Research Procedia, 12, 634-643, 2016.
• Navarro C, Roca-Riu M, Furió S, Estrada M. “Designing new models for energy efficiency in urban freight transport for smart cities and its application to the Spanish case”. Transportation Research Procedia, 12, 314-324, 2016.
• Małecki K, Iwan S, Kijewska K. “Influence of intelligent transportation systems on reduction of the environmental negative impact of urban freight transport based on Szczecin example”. Procedia-Social and Behavioral Sciences, 151, 215-229, 2014.
• Taniguchi E. “Concepts of city logistics for sustainable and liveable cities”. Procedia-social and behavioral sciences, 151, 310-317, 2014.
• Thompson RG, Hassall K. “Implementing high productivity freight vehicles in urban areas”. Procedia-Social and Behavioral Sciences, 151, 318-332, 2014.
• Zidi A, Bouhana A, Fekih A, Abed M. “Personalization of Itineraries search using Ontology and Rules to Avoid Congestion in Urban Areas”. IFAC Proceedings Volumes, 47(3), 4196-4200, 2014.
• Cagliano AC, Gobbato L, Tadei R, Perboli G. “Its for e-grocery business: the simulation and optimization of urban logistics project”. Transportation Research Procedia, 3, 489-498, 2014.
• Lu M. “Advanced Logistics for Sustainable Urban Areas”. Second International Conference on Traffic and Transport Engineering (ICTTE). 2014.
• Tesch C, Clausen U, Wohlgemuth S. “Logistics for decision support in the operation of both terminals and the corresponding yards”, 15th World Multi-Conference on Systemics, Cybernetics and Informatics (WMSCI), Orlando, USA, 19-22 July 2011.
• Oliveira LK, Nunes NTR, Novaes AGN. “Assessing model for adoption of new logistical services: An application for small orders of goods distribution in Brazil”. Procedia-Social and Behavioral Sciences, 2(3), 6286-6296, 2010.
• Ambrosini C, Routhier JL. “Objectives, methods and results of surveys carried out in the field of urban freight transport: an international comparison”. Transport Reviews, 24(1), 57-77, 2004.
• Akao Y, King B, Mazur GH. Quality function deployment: integrating customer requirements into product design. Cambridge, MA: Productivity press, 1990.
• Hauser JR, Clausing D. The house of quality. 1988.
• Chan LK, Wu, ML. “Quality function deployment: A literature review”. European journal of operational research, 143(3), 463-497, 2002.
• Civitas, Policy Note. “Intelligent Transport Systems and traffic management in urban areas”. 2015.
• Cohen B. “Smart city wheel. Retrieved from SMART & SAFE CITY”. 2013.
• Deloitte. “Akıllı Şehirler, Teknolojideki Hızlı İlerlemeler Ekonomimizi ve Toplumu Nasıl Yeniden Şekillendiriyor?”. 2015.
• Ilıcalı M, Toprak T, Özen H, Tapkın S, Öngel A, Camkesen N, Kantarcı M. “Akıcı-Güvenli Trafik için Akıllı Ulaşım Sistemleri”. 2016.
• Goldman T, Gorham R. “Sustainable urban transport: Four innovative directions”. Technology in society, 28(1-2), 261-273, 2006.
• ASCIMER (Assessing Smart Cities in the Mediterranean Region). “Assessment Methodology for Smart City Projects-Application to the Mediterranean Region”. Universidad Politecnica of Madrid (UPM), 2017.
• Chang YH, Yeh CH. “Evaluating airline competitiveness using multiattribute decision making”. Omega, 29(5), 405-415, 2001.
• Chou SY, Chang YH, Shen CY. “A fuzzy simple additive weighting system under group decision-making for facility location selection with objective/subjective attributes”. European Journal of Operational Research, 189(1), 132-145, 2008.
• Beg I. Rashid T. “TOPSIS for hesitant fuzzy linguistic term sets”. International Journal of Intelligent Systems, 28(12), 1162-1171, 2013.