AN ARTIFICIAL NEURAL NETWORK APPROACH FOR THE LOGISTICS CENTER LOCATION SELECTION

Purpose- The importance of the city freight transport is crucial when the sustainable development of the city is considered. City logistics come up against the environmental problems such as traffic congestion, air and noise pollution. The importance of the analyzing and controlling the city logistics activities is evident, considering the effects on the big cities that have a considerable population, a developed industry, and considerable logistics activities. The location selection decision of the logistics center is crucial in terms of the efficient design of the network. The aim of this study is to develop a system that intended to help decision makers decide the feasibility of the potential location for the logistics centers by entering the input values for the parameters of the location. Methodology- In this study, the factors such as accessibility, costs, land feasibility, socio-economic and environmental factors is considering as the critical factors in selecting the most suitable logistics center location. An artificial neural network approach is proposed for the location selection problem of the logistics centers. Findings- The findings indicate that the parameter associated with the socio-economic and environmental impact is crucial on logistics center location decision. The output values of the neural network is compared with the real values of the logistics center located in Turkey. The test results indicate that the artificial neural network gives feasible outputs by entering the input values that are not include in the training datasets.Conclusion- The factors affecting logistics center location decision are socio-economic and environmental, accessibility, land feasibility and costs, respectively. As a result of this study, the developed neural network is not only help the decision makers to choose the feasible logistics center location through the alternatives but also decide the feasibility of any location by entering the value of the input parameters.

Keywords:

Logistics center artificial neural network, location selection,

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Aksoy, A., Öztürk, N. 2011, “Supplier selection and performance evaluation in just-in-time production environments”, Expert Systems with Applications, vol. 38, pp. 6351-6359.
Arıkan, F. 2012, “Lojistik Köyler ve Bir Uygulama”, Bahçeşehir Üniversitesi Fen Bilimleri Enstitüsü Kentsel Sistemler ve Ulaştırma Yönetimi, Yüksek Lisans Tezi, İstanbul.
Bamyacı, M. 2008, “Modern Lojistik Yönetimi: Organize Lojistik Bölgeleri için Bir Yer Seçimi Modeli”, İstanbul Üniversitesi Fen Bilimleri Enstitüsü Deniz Ulaştırma İşletme Mühendisliği Anabilim Dalı, Doktora Tezi, İstanbul.
Benjelloun, A., Crainic T.G. 2009, “Trends, Challenges, and Perspectives In City Logistics”, Buletinul AGIR, no. 4, pp. 45-51.
Can, A. M. 2012, “Çok Kriterli Karar Verme Teknikleri ile Samsun Lojistik Köyü Yerinin Belirlenmesi”, Erciyes Üniversitesi Fen Bilimleri Enstitüsü Endüstri Mühendisliği Anabilim Dalı, Yüksek Lisans Tezi, Kayseri.
Crainic, T.G., Ricciardi, N., Storchi, G. 2009, “Models for evaluating and planning city logistics systems”, Transportation Science, vol. 43, pp. 432-454.
Demiroğlu, Ş., Eleren, A. 2014, Küresel lojistik köyleri ve Türkiye’de kurulması planlanan lojistik köy bölgelerinin ÇKKV yöntemleriyle belirlenmesi”, Dumlupınar Üniversitesi Sosyal Bilimler Dergisi, sayı 42, s. 189-202.
EasyNN-plus Help, The user interface manual.
Elevli, B. 2014, “Logistics freight center locations decision by using Fuzzy- PROMETHEE”, Transport, vol. 29, pp. 412-418.
Elgün, M. N. 2011, “Uluslararası Taşıma Ve Ticarette Lojistik Köylerin Sağladığı Rekabet Avantajları: Bir Model Önerisi”, Afyon Kocatepe Üniversitesi Sosyal Bilimleri Enstitüsü Işletme Ana Bilim Dalı, Doktora Tezi, Afyonkarahisar.
Eryürük, S. H. 2010, “Tekstil ve Konfeksiyon Sektörleri Arasında Etkin Lojistik Faaliyetlerinin Gerçekleştirilmesi Amacıyla Bir Lojistik Merkez Yer Seçimi Ve Tasarımı”, İstanbul Teknik Üniversitesi Fen Bilimleri Enstitüsü Tekstil Mühendisliği Ana Bilim Dalı, Doktora Tezi, İstanbul.
Görgülü, H. 2012, “Lojistik Köyler ve Konya Uygulaması”, Bahçeşehir Üniversitesi Fen Bilimleri Enstitüsü Kentsel Sistemler ve Ulaştırma Yönetimi, Yüksek Lisans Tezi, İstanbul.
Haykin, S. 2008, “Neural Networks and Learning Machines”, 3rd Edition, Prentice Hall.
Hua, J., Qi-hong., L. 2009, “Study on logistics center location judgement based on Aritificial Neural Networks”, First International Workshop on Education Technology and Computer Science, pp. 346-348.
İnaç, H. 2012, “İstanbul’un Kentsel Lojistik Analizi ve Çözüm Önerilerinin AHP ile Değerlendirilmesi”, Bahçeşehir Üniversitesi Fen Bilimleri Enstitüsü Kentsel Sistemler ve Ulaştırma Yönetimi, Yüksek Lisans Tezi, İstanbul.
Li, Y., Liu, Y. 2011, “The Application of Fuzzy Neural Network in Distribution Center Location”, International Conference on Energy Systems and Electrical Power, no: 13, 6458-6463.
Lin, J. 2012, “The application of logistic center location based on Fuzzy BP Neural Network” Service Systems and Service Management, 9th International Conference.
Önden, İ., Eldemir, F., Çancı, M. 2015, “Logistics center concept and location decision criteria”, Sigma Journal Engineering and Natural Sciences, vol. 33, pp. 325-340.
Önden, İ., Acar, A. Z., Eldemir, F. 2016, “Evaluation of the logistics center locations using a multi-criteria spatial approach”, Transport, Article in press, pp. 1-13.
Önder, E., Yıldırım, B. F. 2014, “VIKOR method for ranking logistic villages In Turkey”, Yönetim ve Ekonomi Araştırmaları Dergisi, sayı 23, s. 293-314.
Özceylan, E., Erbaş, M., Tolon, M., Kabak, M., Durgut, T. 2016, “Evaluation of freight villages: A GIS-based multi-criteria decision analysis”, Computers In Industry, vol. 76, pp. 38-52.
Pamucar, D., Vasin L., Atanaskovic, P., & Milicic, M. 2016, “Planning the city logistic terminal location by applying the green p-median model and type-2 Neurofuzzy Network”, Computational Intelligence and Neuroscience, vol. 2016, pp. 1-15.
Peker, İ. 2012, “Analitik Ağ Süreci yöntemiyle lojistik merkez yer seçimi: Trabzon örneği”, Karadeniz Teknik Üniversitesi İşletme Ana Bilim Dalı, Doktora Tezi, Trabzon.
Peker, İ., Baki, B., Tanyaş, M., Ar, İ. M. 2016, “Logistics center site selection by ANP/BOCR analysis: A case study of Turkey”, Journal of Intelligent & Fuzzy Systems, vol. 30, pp. 2383–2396.
Rao, C., Goh, M., Zhao, Y., Zheng, J. 2015, “Location selection of city logistics centers under sustainability”, Transportation Research, vol. 36, pp. 29-44.
Sürmeli, G. 2013, “Lojistik Merkezi Seçimine Yönelik Bulanık Çok Ölçütlü Karar Verme Modeli: Doğu Anadolu Bölgesi için bir uygulama”, Yıldız Teknik Üniversitesi Fen Bilimleri Enstitüsü Endüstri Mühendisliği Ana Bilim Dalı Sistem Mühendisliği, Yüksek Lisans Tezi, İstanbul.
Taniguchi, E., Thompson, R. G., Yamada, T., Duin, R. V. 2001, “City Logistics, Network Modelling and Intelligent Transport Systems”, Elsevier, Pergamon, Oxford, 252 pp.
Tanyaş, M., Arıkan, F. 2013, “Bursa İli Lojistik Merkez Ön Fizibilite Raporu”, T.C. Kalkınma Bakanlığı ve Bursa Eskişehir Bilecik Kalkınma Ajansı, Bursa.
Villamizar, A. F. M., Torres, J. R. M., Padilla, N., H. 2014, “Mathematical programming modeling and resolution of the location-routing problem in urban logistics”, Ing. Univ. Bogotá, Colombia, vol. 18, pp. 271-289.
Kayıkçı, Y. 2010, “A conceptual model for intermodal freight logistics centre location decisions”, Procedia Social and Behavioral Sciences, vol. 2, pp. 6297–6311. URL 1, www.tcdd.gov.tr.
Yuxiang, S., Qing, C., Zhenhua, W. 2009, “Logistics distribution center location evaluation based on Genetic Algorithm and Fuzzy Neural Network”, Computational Intelligence and Intelligent Systems, vol. 51, pp. 305-312.
Zak, J., Weglinski, S. 2014, “The selection of the logistics center location based on MCDM/A methodology”, Transportation Research Procedia, vol. 3, pp. 555-564.