Abstract

Tez (Yüksek Lisans) -- İstanbul Teknik Üniversitesi, Fen Bilimleri Enstitüsü, 2006 Thesis (M.Sc.) -- İstanbul Technical University, Institute of Science and Technology, 2006 Bu çalışmada, Kentsel Lojistik ve Lojistik Köy kavramları ele alınıp, kentsel lojistik kavramı çerçevesinde geliştirilen optimum modelleme yöntemlerinin karşılaştırmalı olarak değerlendirilmesinin yapılması ve incelenen modeller neticesinde İstanbul’da organize lojistik bölge kurulumu için büyüklük ve lokasyon tayini hedeflenmiştir. Endüstriyel üretim alanları, organize sanayi bölgeleri, küçük sanayi bölgeleri ve kooperatifler, serbest bölge ve limanlar; yük üretim, tüketim ve geçiş noktaları kentsel alanların çevresinde yoğunlaşmaktadır. Bu durum, lojistik maliyetlerin yüksek olması, trafik ve gürültü gibi çevresel kirlilikler ve diğer verimsizliklere neden olmaktadır. Kesin Ağırlık Merkezi veya Taşıma Maliyetlerinin En Küçüklenmesi yöntemi ile yer seçimi kararı, taşıma modu, ağırlık ve mesafeye dayalı taşıma maliyetine bağlıdır. Bu modelde bilinenler, tedarik ve teslimat kaynaklarının koordinatları, yük miktarları ve bilinmeyen ise kurulacak Organize Lojistik Bölge’nin koordinatlarıdır. Bu problemde amaç fonksiyonu toplam taşıma maliyetinin minimum yapılması olarak tanımlanır. Elde edilen çözüm bize kurulması gereken OLB’nin koordinatlarını verecektir. Uygulama esnasında klasik algoritma ve yöntemlerin uygulanabilirliğinin sağlanabilmesi adına sınırlı sayıda nokta tespit edilmiş ve bu noktalar arasında OLB’nin tayini yapılmaya çalışılmıştır. In this study, optimum modelling techniques, which were developed for City Logistics, were examined comparatively including the discussion of Urban Logistics and Freight Village concepts. Moreover, determination of optimal location and size of such logistics terminals in Istanbul was aimed. Industrial production areas, industrial zones, small industrial zones and co-operative societies, free zones and ports; freight production, consumption and crossing points are on the increase in urban areas. This situation causes the high logistics costs, undesirable environmental factors such as traffic and high noise levels and other lacks of productivity. Determining optimal location with P-center problems or minimizing transportation costs methods are dependent on transmission mode, freight and transport costs that change with transmission distances. In these models, the coordinates of supply and delivery points and weights are known and coordinates of industrial zone are unknown. Objective function is described as minimizing total transmission costs. The solution set will give us the coordinates of the logistics terminal which is thougt to be build. This problem was studied with limited industrial zone and freight transport points in order to use the classical algorithms and methods and the coordinates of logistics terminal were calculated just considering these points. Yüksek Lisans M.Sc.

Abstract

Increasingly significant freight transport had led to larger and more complex transport chains. More specifically, intermodal transport has arisen as a desirable alternative to long-haul road transport, as it creates opportunities for cost reduction and to decrease both polluting emissions and road congestion. Hence, achieving good levels of service in intermodal dedicated structures is of paramount importance for the success of this transport option. The global objective of this research is to determine the capacity of the Freight Village of Turin. This is motivated by future changes in traffic demand, related with the neighboring Port of Savona-Vado. The role of freight villages and other logistics centers is becoming progressively more substantial with saturating sea ports focusing on handling operations. Existing literature shows success in intermodal transport highly depends on terminal performance. To fulfil the already mentioned objective, a simulation model was developed, based on discrete-event methodology, which simulates rail and handling operation inside the freight village. The model is then used to test several scenarios with the purpose of investigating variation in operation techniques and resources and the respective impact it has on comprehensive capacity. Confronting the tested scenarios allowed to comprehend the inefficiencies of both rail and handling processes, hence concluding that locomotive operation presents the most limiting factor. Furthermore, by combining different operation conditions and resources, it was possible to conclude how these affect final capacity and overall performance. Document type: Article