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Yayın Optimal investment levels to eliminate inventory inaccuracy in a two-level supply chain(Istanbul Technical Univ, 2007) Uçkun, Canan; Karaesmen, Ahmet Fikri; Savaş, SelçukInventory inaccuracy is a major problem in supply chains. RFID technology is anticipated to alleviate this problem at the expense of the required hardware and software investment. For a supply chain consisting of single supplier and multiple warehouses, we investigate the optimal levels of investment in order to decrease inventory inaccuracy. The analysis yields in-sights on the relative benefits of RFID implementation depending on factors such as demand and inaccuracy variability, financial parameters and supply chain structure.Yayın What would normalisation of economic relations between Mashrek countries, Turkey and Israel imply?(Blackwell, 2007-04) Tovias, Alfred; Kalaycıoğlu, Sema; Dafni, Inon; Ruben, Ester; Herman, LiorThis article examines the potential for economic cooperation among Mashrek countries, Turkey and Israel in the fields of trade in goods and services both separately and across-field. It first describes the macroeconomic features of the region and then estimates the overall potential for inter-industry trade in goods by estimating gravity equations for each country separately and the potential for intra-industry trade using Grubel-Lloyd indices. The article also examines the potential for trade in specific services, namely information and computer technology, transport, financial and health services.Yayın Comparison of evolutionary techniques for Value-at-Risk calculation(Springer-Verlag Berlin, 2007) Uludağ, Gönül; Etaner Uyar, Ayşe Şima; Senel, Kerem; Dağ, HasanThe Value-at-Risk (VaR) approach has been used for measuring and controlling the market risks in financial institutions. Studies show that the t-distribution is more suited to representing the financial asset returns in VaR calculations than the commonly used normal distribution. The frequency of extremely positive or extremely negative financial asset returns is higher than that is suggested by normal distribution. Such a leptokurtic distribution can better be approximated by a t-distribution. The aim of this study is to asses the performance of a real coded Genetic Algorithm (CA) with Evolutionary Strategies (ES) approach for Maximum Likelihood (ML) parameter estimation. Using Monte Carlo (MC) simulations, we compare the test results of VaR simulations using the t-distribution, whose optimal parameters are generated by the Evolutionary Algorithms (EAs), to that of the normal distribution. It turns out that the VaR figures calculated with the assumption of normal distribution significantly understate the VaR figures computed from the actual historical distribution at high confidence levels. On the other hand, for the same confidence levels, the VaR figures calculated with the assumption of t-distribution are very close to the results found using the actual historical distribution. Finally, in order to speed up the MC simulation technique, which is not commonly preferred in financial applications due to its time consuming algorithm, we implement a parallel version of it.
