Prospects for Research in Transport and Logistics on a Regional: Global Perspective (I: February 2009: İstanbul: Turkey)

"International Conference on Prospects for Research in Transport and Logistics on a Global - Regional Perspective" has undertaken the challenge to host very important experts and practitioners of Transport and Logistics from a large spectrum of countries. In our opinion, the conference has fulfilled the purpose of establishing an International Society; "Eurasian and Eastern Mediterranean Institute of Transportation and Logistics Association (EMIT)" that is expected to have a very promising role in the Eurasian and Eastern Mediterranean countries. The purpose of the Association is to contribute to establishing and developing the exchange of research work between all parts of the world in all fields of transportation and logistics. This proceedings book consists of 13 chapters, grouping the contributed papers into the following categories: Global Issues in Logistics and Transportation (3 papers), Regional Issues in Logistics and Transportation (2 papers), Education and Training in Logistics and Transportation (2 papers), Supply Chain Management (3 papers), Sustainable Transport Policies, Traffic Engineering (4 papers), Evaluation of Public Policies, Network Models and Environment (4 papers), Contemporary Topics in Transport and Logistics (7 papers), Transport Planning and Economics (3 papers), Planning, Operations, Management and Control of Transport and Logistics (3 papers), Transport Modeling (5 papers), Freight Transportation and Logistics Management (7 papers), Transport and Land Use (3 papers), Transport Infrastructure and Investment Appraisal (2 papers) It can be readily seen from this volume of selected papers that all papers do elaborate on rather timely problems in the fields of expertise related to Transport and Logistics, which have a considerable global importance.TÜBİTAK; Doğuş Üniversitesi ; Uluslararası Nakliyeciler Derneği ; İDO ; Tırsan ; Türk Hava YollarıCommittees, i -- Words of Welcome and Gratitude, ii -- Introduction, iii -- Chapter 1 Global Issues in Logistics and Transportation, 1 -- Potential to Reduce GHG through Efficient Logistic Concepts, 3 -- Werner Rothengatter -- A methodological framework for the evaluation and prioritisation of multinational transport projects: the Case of euro-asian transport linkages, 21 / Dimitrios TSAMBOULAS, Angeliki KOPSACHEILI -- Container port throughput performance - case study: Far east, north west european and mediterranean ports, 29 / Vesna DRAGOVIC-RADINOVIC, Branislav DRAGOVIC, Maja SKURIC, EmirĞIKMIROVlC and Ivan KRAPOVIC -- Chapter 2 Regional Issues in Logistics and Transportation, 35 -- Logistics service providers in turkey: A panel data analysis, 37 / Emel AKTAŞ, Füsun ÜLENGİN, Berrin AĞARAN, Şule ÖNSEL -- Milestones in the process of survey preparation for the logistics sector: case study for Istanbul, Turkey, 43 / Evren POSACI, Darçın AKIN -- Chapter 3 Education and Training in Logistics and Transportation, 51 -- Education in transport and logistics in an age of global economy, 53 / Yücel Candemlr -- The role of education and training in the supply chain sector, 59 / David Maunder -- Chapter 4 Supply Chain Management, 64 -- Modeling reverse flows in a closed -loop supply chain network, 67 / Vildan ÖZKIR, Önder ÖNDEMİR and Hüseyin BAŞLIGİL -- Strategic analysis of green supply chain management practices in T urkish automotive industry, 73 / Gülçin BÜYÜKÖZKAN and Alişan ÇAPAN -- A new framework for port competitiveness: the network approach, 79 / Marcella DE MARTINO, Alfonso MORVILLO -- Chapter 5 Sustainable Transport Policies, Traffic Engineering, 87 -- Clean transport: innovative solutions to the creation of a more sustainable urban transport system, 89 / Ela BABALIK-SUTCLIFFE -- Effects of urban bottlenecks on highway traffic congestion: case study of Istanbul, Turkey, 95 / Darçın AKIN and Mehtap ÇELİK -- Establishing an effective training module for IMDG code in MET institutions, 105 / Kadir CICEK, Metin CELIK -- An investment decision aid proposal towards choice of container terminal operating systems based on information axioms, 109 / Metin CELIK, Selcuk CEBI -- Chapter 6 Evaluation of Public Policies, Network Models and Environment, 115 -- Possibilistic linear programming approach for strategic resource planning, 117 / Özgür KABAK, Füsun ÜLENGİN -- A structural equation model for measuring service quality in passenger transportation, 125 / G.Nilay YÜCENUR and Nihan ÇETİN DEMİREL -- Analysis of potential gain from using hybrid vehicles in public transportation, 133 / İrem DÜZDAR and Özay ÖZAYDIN -- Optimization of e-waste management in Marmara region - Turkey, 141 / İlke BEREKETLİ, Müjde EROL GENEVOIS -- Chapter 7 Contemporary Topics in Transport and Logistics, 147 -- Future prospects on urban logistic research, 149 / Rosârio MACÂRIO, Vasco REIS -- An analyze of relationship between container ships and ports development, 155 / Branislav DRAGOVIC, Vesna Dragovic-Radinovic, Dusanka Jovovic, Romeo Mestrovic and Emir Ğikmirovic -- A holistic framework for performance measurement in logistics management, 161 / Yasemin Claire ERENSAL -- Heuristics for a generalization of tsp in the context of PCB assembly, 167 / Ali Fuat ALKAYA and Ekrem DUMAN -- Premium e-grocery: Exploring value in logistics integrated service solutions, 173 / Burçin BOZKAYA, Ronan De KERVENOAEL and D. Selcen Ö. AYKAÇ -- T ravelers response to VMS in the Athens area, 179 / Athena TSIRIMPA and Amalia POLYDOROPOULOU -- Regional airports and local development: the challenging balance between sustainability and economic growth, 189 / Rosârio MACÂRIO and Jorge SILVA -- Chapter 8 Transport Planning and Economics, 195 -- How financial constraints and non-optimal pricing affect the design of public transport services, 197 / Sergio R. Jara-Diaz and Antonio Gschwender -- Revenue management for returned products in reverse logistics, 203 / Mesut KUMRU -- Intra-city bus planning using computer simulation, 211 / Reza AZIMI and Amin ALVANCHI -- Chapter 9 Planning, Operations, Management and Control of Transport and Logistics, 217 -- A review of timetabling and resource allocation models for light-rail transportation systems, 219 / Selmin D. ÖNCÜL, D. Selcen Ö. AYKAÇ, Demet BAYRAKTAR and Dilay ÇELEBİ -- An approach of integrated logistics HMMS model under environment constraints and an application of time scale, 225 / Fahriye Uysal, Ömür Tosun, Orhan Kuruüzüm -- Freight transport planning with genetic algorithm based projected demand, 231 / Soner HALDENBILEN, Ozgur BASKAN, Huseyin CEYLAN and Halim CEYLAN -- Chapter 10 Transport Modeling, 239 -- Inverse model to estimate o-d matrix from link traffic counts using ant colony optimization, 241 / Halim CEYLAN, Soner HALDENBILEN, Huseyin CEYLAN, Ozgur BASKAN -- The impact of logistics on modelling commercial freight traffic, 251 / Ute IDDINK and Uwe CLAUSEN -- A comparative reviewof simulation-based behavior modeling for travel demand generation, 257 / Seda Yanık, Mehmet Tanyaş -- An efficiency analysis of turkish container ports using the analytic network process, 269 / Senay OĞUZTİMUR, Umut Rıfat TUZKAYA -- A multi-objective approach to designing a multicommudity supply chain distribution network with multiple capacities, 277 / Gholam Reza Nasiri, Hamid Davoudpour and B.Karimi -- Chapter 11 Freight Transportation and Logistics Management, 283 -- Evaluation of turkey’s freight transportation, 285 / Burcu KULELİ PAKand BaharSENNAROĞLU -- Short sea shipping, intermodality and parameters influencing pricing policies in the Mediterranean region: The Italian context, 291 / Monica GROSSO, Ana-Rita LYNCE, Anne SILLA, Georgios K. VAGGELAS -- Relevant strategic criteria when choosing a container port - the case of the port of Genoa, 299 / Monica Grosso, Feliciana Monteiro -- Determination of optimum fleet size and composition - A case study of retailer in Thailand, 307 / Terdsak RONGVIRIYAPANICH and Kawee SRIMUANG -- New container port development: forecasting future container throughput, 313 / Dimitrios TSAMBOULAS, Panayota MORAITI -- Sea port hinterland flows and opening hours: the way forward to make them match better 319 / Marjan BEELEN, Hilde MEERSMAN, Evy ONGHENA, Eddy VAN DE VOORDE and Thierry VANELSLANDER -- International road freight transport in Germany and the Netherlands driver costs analysis and French perspectives, 327 / Laurent GUIHERY -- Chapter 12 Transport and Land Use, 335 -- Land rent and new transport infrastructure: How to manage this relationship?, 337 / Elena SCOPEL -- Effects of pavement characteristics on the traffic noise levels, 345 / Aybike ONGEL and John HARVEY -- Fuzzy medical waste disposal facility location problem, 351 / Yeşim KOP, Müjde EROL GENEVOIS and H. Ziya ULUKAN -- Chapter 13 T ransport Infrastructure and Investment Appraisal, 357 -- Agents’ behavior in financing Italian transport infrastructures, 359 / Paolo BERIA -- Free trade agreements in the mediterranean region: a box-cox analysis, 367 / Matthew KARLAFTIS, Konstantinos KEPAPTSOGLOU and Dimitrios TSAMBOULA

Senaryo analizi için dinamik bir yaklaşım önerisi

This paper proposes a dynamic scenario analysis approach in order to understand the uncertainties about the future.  The development of alternative futures/scenarios is an important part of strategy making. This paper's objective is to propose an improved scenario analysis model based on Powell's scenario analysis approach, namely, EFAR (Extended Field Anomaly Relaxation) (Powell, 1997). This improved model is referred as REFAR (Revised EFAR) hereinafter and is expected to provide a useful guide both in public and private organizations, during their scenario planning activities. REFAR aims to eliminate the basic drawbacks of EFAR and improve its efficiency by the help of cognitive maps and artificial neural networks. In the application part of the research, REFAR is applied to Turkey's inflation analysis. Initially the probable scenarios are built, and the transitions between them are analysed. The basic scenarios finally reached through REFAR, the transition among each key scenarios as well as among the scenarios grouped under each key scenario are explained in detail. The scenarios within each key scenario clusters provide a detailed picture of all the possible futures that may be encountered. Using them, it is also possible to see the possible transition and the resulting changes that will occur within the other scenarios in the same key cluster and in the scenarios of other clusters that the scenario of interest is in direct relation with. Keywords: Cognitive mapping, neural networks, scenarios.Bu çalışmada, gelecekteki belirsizlikleri anlamaya yönelik olarak kullanılan senaryo analizi için dinamik bir yaklaşım önerilmektedir. Powell (1997) tarafından ortaya konan EFAR (Durum Bozukluklarının Giderilmesine Yönelik Bir Yaklaşım / Extended Field Anomaly Relaxation) modeli; senaryo analizine dinamik bir yapı kazandırmıştır. Ancak bazı zayıf yönleri mevcuttur ve geliştirilmeye açıktır. Bu amaçla, bu çalışmada EFAR yaklaşımındaki zayıf yönleri gidermeyi ve böylece onu, daha etkinleştirmeyi hedefleyen yeni bir model: REFAR (Düzeltilmiş / Revised EFAR) modeli önerilmektedir. Bu doğrultuda bilişsel haritalar ve yapay sinir ağlarından yararlanılmıştır. Uygulamada REFAR modeli aracılığıyla, Türkiye’de enflasyon konusunda karar vericilere destek olabilecek nitelikte dinamik bir senaryo analiz yapısı oluşturulmuştur. Anahtar Kelimeler: Bilişsel haritalar, senaryolar, yapay sinir ağları

Possibilistic linear programming approach for fuzzy Supply Chain Planning

Son yıllarda, küreselleşmeyle artan rekabet ile birlikte, Tedarik Zinciri Planlamanın (TZP) önemi artmaktadır. Bu nedenle; TZP’de stratejik kararlarının verilmesi çok büyük önem taşımaktadır. Gerçek problemlerin hepsinde görüldüğü gibi, tedarik zincirinin ilgili süreçlerinde de belirsizlikler ile karşılaşılmaktadır. Bundan ötürü; TZP modellerinde belirsizliklerin göz ardı edilmemesi gerekmektedir. Literatürde TZP’deki belirsizlikleri modelleyen çalışmalarda uzun dönemli stratejik kararların kesin olarak verildiği ve bunların orta ve kısa vadede revize edilmeleri gerektiği tespit edilmiştir. Bu çalışmada, uzun dönemli kaynak atama, ürün tedariki ve üretim kararlarının verilebilmesi için bir Olabilirsel Doğrusal Programlama (ODP) modeli geliştirilmiştir. ODP modelini kullanmanın temel amacı, tedarikçi ilişkilerinde ve üretim planlamada esneklik sağlamak üzere bulanık kararların verilmesini olanaklı kılmaktır. Bu yüzden önerilen ODP’de, sadece talep ve verim oranları gibi kritik TZP girdileri değil aynı zamanda satış miktarı, üretim miktarı ve tedarik miktarı gibi karar değişkenleri de bulanık kabul edilmiştir. Önerilen ODP’nin amacı firmanın tedarik zinciri faaliyetleri sonucunda oluşan kârı en büyüklemektedir. Çalışmada ODP’yi çözmek için DP modeline çevrilmesi önerilmiştir. Bu amaçla girdi parametreleri ve karar değişkenleri üçgen bulanık sayılar ile ifade edilmiştir. ODP’de önerilen amaç fonksiyonu ve kısıtlar, üçgen bulanık sayılar için geliştirilen toplama ve çarpma işlemleri ile büyüktür/küçüktür ilişkileri ile DP’ye çevrilmiştir. Çalışmada ayrıca önerilen modelin etkinliği hipotetik bir örnek üzerinde gösterilmiştir. Anahtar Kelimeler: Tedarik Zinciri Planlama, olabilirsel doğrusal programlama, bulanık modelleme.The interest in Supply Chain Planning (SCP) has recently raised due to the fact that the opportunity of an integrated planning of the supply chain (SC) can increase the profitability, reduce production and outsourcing costs and enhance customer service levels, so that the enterprises can cope with increasing competitiveness introduced by the market globalization. A SC is an integrated system which synchronizes a series of inter-related business processes in order to convert raw materials into the specified finished products and distribute and promote these products to retailers or customers. Supply chain planning problems are due to uncertainties like the other real life problems. Uncertainties that affect the SCs can be categorized in two groups: (i) environmental uncertainties, and (ii) system uncertainties. Environmental uncertainties include supply quantity, raw material costs, lead times, and demand product price while system uncertainties contain operation efficiency, resource usage efficiency, labor cost, production capacity, and stock level. Among these uncertainty types, demand has been the most important and extensively studied source of uncertainty. The emphasis on incorporating demand uncertainty into the planning decisions is appropriate given the fact that effectively meeting customer demand is what mainly drives most SCP initiatives. Furthermore, demand is the main source of uncertainties as the fluctuations of it affects the production system and suppliers gradually. The main idea of the proposed model is to make uncertain and therefore flexible decisions to cope with the uncertainties revealed in strategic SCP. Demand affects system uncertainty in which some other types of uncertainty also exist. System uncertainty and supply uncertainty mutually affects each other. In this circumstances to make crisp decisions may cause irrelevant or irreversible long term decisions that will need huge revisions in medium or short term. In this paper a Possibilistic Linear Programming (PLP) model is proposed to support strategic decisions of the enterprises concerning the production resources utilization and outsourcing. In order to deal with the external and internal uncertainties fuzzy inputs and fuzzy outputs are considered. The problem examined in the paper is  described as; Given: (1) A supply chain that is the integration of the focal enterprise, its current suppliers and customers, as well as the potential suppliers and customers, and related products, semi-products and raw materials (in the rest of the paper "product" will be used for these three concepts),(2) Resources used to produce the products as well as their costs and capacity levels,(3) Outsourced products and other outsourcing opportunities, as well as their costs,(4)Production and outsourcing yield rates of product. Using the inputs defined above, the model proposed helps the enterprise make decisions about the following strategic questions: (1) Which product should be produced internally? (2) Which resources should be utilized to the production of which product? (3) Which products should be outsourced, and how much? (4) Demands of which market should be satisfied? The proposed PLP contains fuzziness in some of the constraint parameters and in all decision variables. The objective of the PLP model is to maximize the profit of enterprise's SC facilities. To solve the proposed PLP model it is suggested to be transformed into a linear programming model, which can be solved easily with the least mathematical effort. Therefore the inputs and the decision variables of the model are represented by triangular fuzzy numbers. Then  the summation, multiplication operations as well as the greater than and less than relations that are defined for triangular fuzzy numbers are employed to transform the PLP to a linear program. The proposed PLP model is then applied in a hypothetical example to evaluate the applicability and validity of the model and the solution methodology. As a result of the application it is realized that the uncertainty in the outputs depends on the uncertainty in the inputs. The uncertainty in the inputs affects both the uncertainty and the amount of profit. Under these circumstances the model aims to decrease the uncertainty on the decisions and increase the profit. Consequently model is proved to give satisfactory results. Keywords: Supply Chain Planning, possibilistic linear programming, fuzzy sets

Predicting company merger and acquisition with the help of artificial neural networks

Değişen pazar yapısı ve rekabet koşulları şirketleri, yeni çözümler geliştirme zorunluluğu ile karşı karşıya bırakmıştır. Birleşmeler, şirketlerin yeni çözüm arayışları sonucu gündeme gelmiş buluşlardan bir tanesidir. Faaliyetlerin daha etkin yürütülmesi, faaliyet sinerjisi ve finansal sinerji elde edilmesi, yönetim etkinliğinde artış, piyasa payı, ürün geliştirme ve dağıtım sistemindeki ilerlemeler, marka, patent birleşmelerin başlıca nedenlerini oluşturur. Birleşmelerin doğru bir strateji olabilmesi için, birleşilecek veya satın alınacak şirket seçiminin, çok iyi analiz edilmesi gerektiği, bu makalede önemle vurgulanmıştır. Birleşmeler sağlıklı yapılması durumunda anlamlı olacaktır. Bu da birleşme sürecinde doğru tekniklerin kullanılması anlamını taşır. Makale kapsamında, şirketleri birleşmeye iten nedenler ve birleşen firmalarda performans artışının gerçekleştiği, stratejik planlamanın şirket birleşmeleri ile olan ilintisi anlatılmış, birleşme süreci yapay sinir ağları ile analiz edilmiş, karar vericiye sunulmak üzere, birleşme için bir yapay sinir ağı modeli oluşturulmuş, modelin oluşturulmasında MATLAB yazılımı kullanılmıştır. Neden sinir ağları sorusunun cevabı ise, onun teori gereksinimi esnektir, araştırma yaklaşımı kuralcı değildir ve bilinmeyeni sunuş şekli bulanık küme tabanlıdır ve en önemli özelliği gerçek dünya problemlerine uygulanabilir olmasıdır. Türkiye’de şirket birleşmeleri henüz gelişme aşamasındadır ve tam anlaşılamamıştır. Yöntemleri konusunda yatırımcılar yeterli bilgiye sahip değildir. Makalenin amacı birleşmenin şirketlerin büyümesi için bir yöntem olduğu, bu sürecin çok iyi analiz edilmesi gerektigi ve en doğru şirketi bulmak için sinir ağları modeli kullanılmasi önerilmiş, Türkiye’nin bir eksikliğine katkı sağlanması amaçlanmıştır.Anahtar Kelimeler: Şirket birleşme ve satınalmaları, yapay sinir ağları, karar verme.Today companies have been engaged in a new pursuit for adapting themselves to the changing market and competition conditions. Mergers are among the trends which have gained wider interest, especially in recent years. In order for the mergers to be a true strategy, the choice of company which will be merged or acquired has to be perfectly analyzed. This process was analyzed via artificial neural networks. Predictor variables selection is important factor about quality of the prediction model to get success. Predictor variables that used as inputs on the neural network model are specified on the basis of six hypotheses being frequently suggested in academic and popular financial literature. These are inefficient management hypothesis, growth resource mismatch hypothesis, industry disturbance hypothesis, size hypothesis, market-to-book hypothesis, price-earning hypothesis. 12 predictor variables that support these hypothesis are average excess return (AER), return on equity (ROE), average turnover (AVTURNOV), average growth (AVGROWTH), average liquidity (AVLIQUID), average leverage (AVLEV), GRDUMMY to see AVGROWTH, AVLIQUID, AVLEV combination, IDUMMY to see sector impact on merger and acquisition, total net book value of asset (SIZE), market-to-book (MTB), price and earnings (PE), average payout (AVPAYOUT). Based on inefficient management hypothesis, inefficiently managed firms are often acquired. AER, ROE, AVTURNOVER are chosen predictor variables to measure firm's management's performance. Growth-research mismatch hypothesis, firms with high growth and low resources or with low growth and high resources are likely to be acquired. The combination of AVGROWTH, AVLIQUID and AVLEV is to form GRDUMMY variable that shows growth-research mismatch impact. IDUMMY variable will be selected based on industry hypothesis to cluster industry impact on merger and acquisition. Based on size hypothesis, smaller firms are more likely to be acquired than larger firms. Size will be selected as a variable as well. Market-to-book hypothesis, the companies have got low market-to-book ratios are likely to be targets and same logic deals with price-earnings hypothesis. For these 12 variables, the data were obtained from COMPUSTAT. Most of the data items for variables were averaged over three to four years prior to observation year. Merger and acquisition process has been analyzed by the artificial neural network. To train the multilayer network to predict the company merger and acquisition, back propagation algorithm has been used. The advantages of back propagation algorithm is provided with a set of examples of proper network behavior where an input to the network and corresponding target output. Working approach of algorithm is to adjust the network parameters in order to minimize the mean square error. The first part of the article deals with the stimulators of the merger, the performance increase in merged companies, and the connection of strategic planning with company mergers. In the second part, artificial neural networks, the method used in the merger and acquisition process, is investigated in scope and structure. The reason for handling the artificial neural networks is that their requirement for a theory is flexible, their research approach is not prescriptive, their presentation of the unknown is fuzzy based, and most importantly, its adaptability to the real world problems. It is a considerably difficult process to determine the layer number and number of nodes on these layers that are optimum for acquiring the best neural network model. Several combinations of hidden layers and nodes are tried before reaching the satisfactory model. This process takes a long time and the optimal network is produced after many trials. The activation acquiring process cannot be realized without the computer support. In this process MATLAB 6.5 is utilized which is explained in the third part. In Turkey company mergers have not reached their maturity and they can not be completely understood. Investors do not have sufficient information on its methods. This article aims to support the view that a merger is a way for a company to grow, and to contribute to a better understanding in Turkey by making use of neural network models for identifying the best company to acquire. Keywords: Merger and acquisiton, artificial neural network, decision making

Solving uncapacitated hub location problem using Hopfield-Tank type artificial neural networks

Merkez üslerin yerleşim noktalarının belirlenmesi ve merkez üsler ağının tasarlanmasını içeren merkez üslerin konumlandırılması problemi konum teorisi alanında yaygın olarak çalışılmaktadır. Bu çalışmada, kapasite sınırlamasının olmadığı, sabit konumlandırma maliyetlerinin olduğu, tek tahsisli merkez üsleri konumlandırma problemi için yapay sinir ağı (YSA) temelli bir çözüm yöntemi önerilmiştir. Ayrıca tavlama benzetimine dayanan bir yöntem de geliştirilmiştir. Yöntemin etkinliğini test etmek için, literatürde sıklıkla kullanılan test veri seti kullanılarak, YSA temelli yöntem için elde edilen sonuçlar ile literatürde yer alan en iyi çözümler ve tavlama benzetiminden elde edilen sonuçlar karşılaştırılmıştır.Anahtar Kelimeler: Merkez üsler, yapay sinir ağları, Hopfield-Tank, tavlama benzetimi. In many transportation and telecommunication networks, the cost of carrying a unit of traffic between two points decreases as the capacity of the connection joining the two points increases. It is possible to facilitate this connection by building dedicated channels between each pair of nodes that communicate with each other. However, this would result in higher costs. Because of this fact, it is often convenient to design networks in which traffic is concentrated on high capacity links, even if this traffic travels longer distances. In order to facilitate the flow of the traffic between nodes so as to decrease the overall cost of transportation, some centers known as hubs are introduced. Airline passenger flow, cargo or postal delivery networks, large telecommunication networks are examples of networks utilizing hubs. The problem addressed in this study is the uncapacitated single allocation hub location problem (USAHLP) in which, given n interacting nodes in a network, hubs are fully interconnected and each spoke is assigned to a unique hub. In this study, a solution method based on an artificial neural network framework for the USAHLP is introduced. The heuristic based on simulated annealing is also developed. To present its effectiveness, the solutions of this ANN-based method is compared with the best solutions presented in the literature and the solutions of simulated annealing based heuristic by considering CAB data set. Keywords: Hub location, artificial neural network, Hopfield-Tank, simulated annealing

A new solution approach for assignment problem

Bu çalışmanın amacı klasik atama problemi için özgün bir çözüm yöntemini tanıtmaktır. Atama probleminin çözümünde en çok bilinen yöntem  Macar yöntemidir. Bu yöntemde maliyet  matrisi her seferinde sistematik bir şekilde yeni bir indirgenmiş matrise dönüştürülerek çözüme gidilmektedir. Yöntem gereği indirgenmiş maliyet matrisindeki sıfır elemanlar en az sayıda çizgi ile kapatılmakta ve buna göre matris üzerinde işlem yapılmaktadır. Ancak problemin büyüklüğü arttıkça ve indirgenmiş maliyet matrisinde sıfır eleman sayısı çoğaldıkça, matristeki sıfır elemanlarını kapatmak üzere gereken en az sayıda çizgi sayısı ve bu çizgilerin nasıl çizilmesi gerektiği sorunu ortaya çıkar. Bu çalışmada Macar yöntemindeki bu boşluğu doldurmak üzere özgün bir yöntem tanıtılmaktadır.Anahtar Kelimeler: Atama problemi, Macar yöntemi.The purpose of this study is to present a new solution approach  for the assignment problem. In assignment problem, there are (m) individuals are to be assigned to (m) jobs. If the individual (i) assigned to job (j), the cost incurred will be (cij), and accordingly the cost matrix is denoted by C. It is desired to find the minimal cost assignment or a one-to-one matching of individuals to jobs. There are many solution methods for this problem, but the simplicity and robutsness of the Hungarian method makes it the best known method among all others. The Hungarian method solves the problem by converting the cost matrix into a reduced matrix systematically at each iteration. A part of this process is finding fewest number of lines to cover all zero elements in the reduced matrix. When the size of the problem increases and reduced matrix contains many zeros, it is a tedious task to find minimum number of lines and the way of drawing them. The Hungarian method has an ambiguity at this point. A solution method is presented in this study to eliminate this ambiguity. A systematic and simple procedure is defined to find the fewest number of lines to cover all zero elements in the reduced matrix. Keywords: Assignment problem, Hungarian method

Predicting unemployment rates with the use of cognitive mappingmethodology and Artificial Neural Networks

Öngörü modellemesi, makro politikaların oluşturulmasında önemli bir karar destek aracı olarak görülmektedir. Bilgisayar teknolojisindeki ilerlemeler sayesinde yapay zeka sistemlerinin karar destek araçları olarak kullanımları da gün geçtikçe artmaktadır. Yapay zeka tekniklerinden Yapay Sinir Ağları yöntemi, öngörü çalışmalarında kullanılabilecek ümit veren bir yöntem olarak araştırmacılar tarafından ilgi görmektedir. Bu çalışmada Bilişsel Haritalar yöntemi ile Yapay Sinir Ağları yöntemleri kullanılarak bir öngörü modeli kurulması çalışması gerçekleştirilmiştir. Çalışmada öngörü veri seti olarak Türkiye’de işsizlik oranları verisi kullanılmıştır. İşsizlik problemi, dünya devletleri için olduğu kadar Türkiye için de en önemli sorunlar arasında yer almaktadır. İşsizliği etkileyen faktörlerin belirlenmesi ve bu faktörler kullanılarak işsizlik tahminleri yapılması, işsizlik sorununa çözüm için hazırlanacak politikaların geliştirilmesinde karar destek bilgisi oluşturulmasına yardımcı olacaktır. Çalışmanın birinci aşamasında bilişsel haritalar yöntemi kullanılarak daha önce Türkiye ile ilgili makroekonomik çalışmaları bulunan beş akademisyenin görüşü alınıp Türkiye’de işsizliği etkileyen faktörler belirlenmiştir. Uzmanlar tarafından belirlenen on bir faktör, çalışmanın ikinci aşamasında çok katmanlı Yapay Sinir Ağı kullanılarak oluşturulan çok değişkenli bir öngörü modeline girdi olarak kullanılmıştır. Çalışmada 1988 ve 2004 yılları arasında dört dönemlik veriler kullanılmıştır. En iyi öngörü modeli, oluşturulan 24 değişik model arasından seçilmiştir. Çalışma sonunda en iyi tahmin modellerine mevsimsellikten arındırılmış veri seti ile ulaşıldığı görülmüştür. Çalışmada aynı zamanda çıktı katmanında kullanılan doğrusal ve doğrusal olmayan aktivasyon fonksiyonlarının, ağ performansına belirgin bir etkisi olmadığı, mevsimsel arındırma ve (0.1;0.9) ölçek aralığı kullanılmasının ise ağ öngörü performansını olumlu etkilediği görülmüştür. Anahtar Kelimeler: Bilişsel haritalar, Yapay Sinir Ağları, işsizlik.Forecasting is accepted as an important tool in the development and application of macro policies. Considering the fact that accurate forecasts help decision makers take better decisions, forecasting studies have started to take growing interest of researchers. By the developments in the computer specifications, artificial intelligence techniques have gained more attention as decision support tools. Among the artificial intelligence techniques, artificial neural networks (ANNs) are seen as promising techniques especially in forecasting applications. In this study, cognitive mapping methodology which is used in capturing the cause-effect relationships in complex causal systems and facilitate understand the interconnections within the elements of the systems by gathering expert knowledge is used in the identification of the factors that affect unemployment in Turkey and ANNs methodology are integrated in order define a prediction model framework. The framework is applied to unemployment rate data sets in Turkey in order to understand the important factors that affect unemployment and to forecast unemployment rate in Turkey. Understanding the factors that affect unemployment and developing forecasting models by the use of these factors can help the decision makers as a decision support mechanism in defining policies to overcome unemployment problem. In the first phase of the study Cognitive Mapping methodology is used in the identification of the factors that affect unemployment in Turkey by taking the views of five different experts who have made research on macroeconomic problems of Turkey.  The eleven variables identified by the experts are used in the second phase of the study as the input data set in developing a multi-variate forecasting model by using ANNs. The research period covers 1988 and 2004. Quarterly data is used in the analysis. To find the best network to forecast the output variables, a design of experiment is made and two different output activation functions; (linear function and nonlinear tangent sigmoid function), two different scaling ranges (-0.9; 0.9 and 0.1; 0.9), seasonal and deseasonalized data is used in the study. Additionally, three different input data structures are used in the study. In the first data structure, all variables identified by the experts are used in the analysis. In the second structure, unemployment rate data in one past period is added to the 11 input variables. In the third input structure, all input variables and unemployment rate are used in their lagged values as the inputs to the network. Therefore a total of 24 different models are tested. The networks are trained using MATLAB software, TRAINGDX training algorithm. To train each network, different numbers of hidden units are used and almost 85 % of the data set is used as the training set. Each run is replicated ten times with different initial weights in order to avoid getting stuck in local minima. Since the data set was not large enough to use a validation set, training is stopped at epoch 1000. The results of the study show that the best network found uses the level values in deseasonalized data sets; a tangent sigmoid function as the output activation function and a scaling range of (0.1;0.9). The structure of the input set is the second structure which includes all the 11 variables identified by the expert and the one past period value of the dependent variable itself. The results show that the specified best neural network model is able to perform satisfactorily within the test set. The test MSE is found to be 0.0015 where the training MSE is 0.0029. Furthermore in the study, the effects of the different activation functions and different scaling ranges and deseasonalization on network prediction performance are tested. The results showed that models using a scaling range of (0.1;0.9) give significantly better average MSE results compared to the models using a scaling range of (-0.9;0.9). For the output activation functions, the test results reveal the mean performances of the models using tangent sigmoid function are not different from each other statistically. The test results also indicate that deseasonalization significantly improves network performance in unemployment rate data. Finally during the analysis it is observed that the networks tend to get over trained as the number of the hidden units increase; this result is in accordance with the findings in previous research on neural networks. The results of the study indicate that ANNs may be considered as promising tools in macroeconomic forecasting studies.  Keywords: Cognitive maps, artificial neural networks, unemployment

Coordination in a two-stage capacitated supply chain with multiple suppliers

Bu çalışmanın amacı, rassal talebe sahip merkezkaç bir tedarik zincirindeki envanter politikalarını kontratlar aracılığıyla koordine etmektir. Ele alınan sistem, sınırlı üretim kapasitesine sahip çoklu bağımsız tedarikçi ve bir üreticiden oluşan iki kademeli merkezkaç bir tedarik zinciridir. Tedarikçiler stok için üretim yapmakta ve envanter yönetiminde temel stok yöntemini kullanmaktadır. Üretici ise sipariş için üretim prensibine göre çalışmaktadır. Tedarikçilerin kapasitesi sınırlı olduğu için, gerekli varsayımlar altında her tedarikçi bir  stok-için-üretim kuyruk sistemi olarak modellenmiştir. Ayrıca, her tedarikçinin ortalama bekleyen sipariş miktarı ve ortalama envanter seviyesi elde edilmiştir. Diğer yandan, üreticinin gelişlerarası sürelerinin yaklaşık dağılımı bulunmuş ve gerekli varsayımlar altında üretici bir  kuyruk sistemi olarak modellenmiştir. Bunun yanı sıra, üreticinin sistemindeki ortalama iş sayısı ve ortalama bekleyen sipariş miktarı hesaplanmıştır. Daha sonra, kuyruk modellerinden elde edilen performans ölçütleri kullanılarak merkezi ve merkezkaç modeller geliştirilmiştir. Bu modellerin eniyi çözümleri karşılaştırıldığında, sadece en düşük temel stok seviyesine sahip tedarikçinin koordine edilmesi gerektiği görülmektedir. Bu nedenle, sadece bu tedarikçi ve üretici arasında kontratlar hazırlanmıştır. Bu çalışmada transfer ödemesine dayalı üç farklı kontrat üzerine çalışılmıştır. Bu kontratlar, bekleyen sipariş maliyetini destekleme kontratı, Pareto iyileştirmeye dayalı transfer ödemesi kontratı ve maliyet paylaşımı kontratıdır. Her kontrat, koordinasyon yeteneği ve Pareto iyileştiren olup olmaması yönünden değerlendirilmiştir. Sonuç olarak, üç kontrat da tedarik zincirini koordine etmektedir. Pareto iyileştirme göz önüne alındığında ise, maliyet paylaşımı kontratının her iki üye tarafından da tercih edilmesi beklenebilir. Anahtar Kelimeler: Tedarik zinciri koordinasyonu, çoklu tedarikçi, kontrat, envanter politikası.The aim of this study is to coordinate the inventory policies in a decentralized supply chain with stochastic demand by means of contracts. The system considered is a decentralized two-stage supply chain consisting of multiple independent suppliers and a manufacturer with limited production capacities. The suppliers operate on a make-to-stock basis and apply base stock policy to manage their inventories. On the other hand, the manufacturer implies a make-to-order strategy. Since the suppliers are capacitated, each supplier is modeled as an  make-to-stock queue under necessary assumptions. Furthermore, the average outstanding backorders and the average inventory level of each supplier are obtained. On the other hand, to model the manufacturer as a queuing system, first an approximate distribution is derived for the interarrival times of the manufacturer. The idea behind the approximation is the expectation that the supplier with the minimum base stock level affects the interarrival times of the manufacturer the most. Then, the manufacturer is modeled as a  queue under necessary assumptions. Moreover, the average number of jobs in the manufacturer's system and the average outstanding backorders at the manufacturer are obtained. After the supply chain has been modeled as a queuing system, the centralized and decentralized systems are taken into account. In the centralized system, there is a single decision maker who tries to optimize the overall supply chain. On the other hand, in the decentralized system, each member tries to optimize his own entity. The centralized system is also considered in this paper since the centralized solution is used as a reference point for the coordination of the decentralized system. In the centralized model, the objective of the single decision maker is to minimize the average total backorder and holding costs per unit time for the overall system. The decision variables are the base stock levels of the suppliers. On the other hand, in the decentralized model, each supplier tries to minimize his average backorder and holding costs per unit time. Since the decision variables are the base stock levels of the suppliers, the manufacturer is not included in the decentralized model. However, the decision of the supplier with the minimum base stock level also affects the manufacturer. When the optimal solutions to the centralized and decentralized models are compared, it is concluded that only the supplier with the minimum base stock level needs coordination. Also, it is found that a coordinating contract has to encourage the relevant supplier to choose a smaller base stock level than his decentralized solution. Therefore, the contracts are prepared accordingly between that supplier and the manufacturer.Three different transfer payment contracts are studied in this paper. These are the backorder cost subsidy contract, the transfer payment contract based on Pareto improvement, and the cost sharing contract. In the backorder cost subsidy contract, the manufacturer covers some part of the supplier's average backorder cost per unit time after the transfer payment. In the transfer payment contract based on Pareto improvement, the manufacturer pays the supplier an amount that makes the manufacturer as well off after the transfer payment as before. Finally, in the cost sharing contract, the manufacturer pays the supplier an amount such that the supplier covers some part of their average total costs per unit time after the transfer payment. Each contract is then evaluated according to its coordination ability and whether it is Pareto improving or not. If a contract is not Pareto improving even it coordinates the supply chain, then at least one of the members will not desire to participate in the contract. The analyses of the contracts point out that all three contracts have the ability to coordinate the supply chain. However, they differ in whether they are Pareto improving or not. It is found that only the backorder cost subsidy contract is not Pareto improving. Among the other two contracts, in the transfer payment contract based on Pareto improvement, only the supplier is better off after the contract and the manufacturer remains the same. On the other hand, in the cost sharing contract, both the supplier and the manufacturer can be better off after the transfer payment for an appropriately selected contract parameter. Therefore, the cost sharing contract seems to be the one that will be preferred by both members. Keywords: Supply chain coordination, multiple suppliers, contract, inventory policy

Fire station location selection for İstanbul

Makale Endüstri Mühendisliği dergisinin "YA/EM 2009 özel sayısı"nda yayımlanmıştır.Özellikle acil hizmetler veren polis, hastane, itfaiye gibi kurumlar için yer seçimi büyük önem taşımaktadır. Uygun bir yer seçimi gerçekleştirilmediği takdirde bunun sonuçları insan hayatını tehlikeye atabilir niteliktedir. İstanbul gibi büyük metropollerde, artan nüfus ve trafik yoğunluğunun yanı sıra bir de metropolün deprem kuşağında olması durumunda, itfaiye araçlarının olay yerine en hızlı şekilde ulaşması hayati önem taşımakta; bu da itfaiye istasyonu yerinin etkin seçimine kritik bir rol yüklemektedir. Bu çalışma; İstanbul Büyükşehir Belediyesi tarafından kararlaştırıldığı gibi, itfaiye teşkilatının her bölgeye en çok beş dakikada erişebilmesi ve kapsama alanının %100 olması hedeflenerek yeni kurulacak olan itfaiye istasyonlarının küme kapsama modeli yardımıyla konumlandırılmasını içermektedir. Bu amaçla bir tamsayı programlama modeli kurulmuş, coğrafi bilgi sistemlerinden elde edilen verilerle model çözülmüş, seçilen yerler için itfaiye kurulması durumunda yangın hizmet düzeyinin değişimi incelenmiştir.For emergency services such as ambulance systems and fire departments, location selection plays a critical role due to the direct impact of these services on human lives. Timeliness plays a primary role in location selection decision of fire stations for large metropolitan cities such as Istanbul with increasing population with a high level of congestion coupled with an imminent earthquake risk. This study is based on a set-covering model for locating new fire stations, which target to serve each area at most in five minutes and improve their coverage area to 100% for Istanbul Municipality Fire Department. Accordingly, a set-covering model is built and solved using the data retrieved from geographical information systems. Finally the change in service level with proposed fire station locations is investigated and further suggestions are provided

Analyzing competitiveness of automotive industry through cumulative belief degrees

Ülengin, Füsun (Dogus Author) -- Önsel, Şule (Dogus Author) -- Kabak, Özgür (Dogus Author) -- Conference full title: 10th International Fuzzy Logic and Intelligent Technologies inNuclear Science Conference, FLINS 2012; Istanbul; Turkey; 26 August 2012 through 29 August 2012This study aims to analyze the automotive industry from competitiveness perspective using a novel cumulative belief degrees (CBD) approach. For this purpose, a mathematical model based on CBD is proposed to quantify the relations among the variables in a system. This model is used to analyze the Turkish Automotive Industry through scenario analysis.SEDEFED (Federation of Industrial Associations), REF (TÜSİAD Sabanci University Competitiveness Forum), and OSD (Automotive Manufacturers Association