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Öğe CMARS and GAM & CQP-Modern optimization methods applied to international credit default prediction(ELSEVIER, 2011) Alp, Özge Sezgin; Büyükbebeci, Erkan; Çekiç, Ayşegül İşcanoğlu; Özkurt, Fatma Yerlikaya; Taylan, Pakize; Weber, Gerhard-WilhelmIn this paper, we apply newly developed methods called GAM & CQP and CMARS for country defaults. These are techniques refined by us using Conic Quadratic Programming. Moreover, we compare these new methods with common and regularly used classification tools, applied on 33 emerging markets' data in the period of 1980-2005. We conclude that GAM & CQP and CMARS provide an efficient alternative in predictions. The aim of this study is to develop a model for predicting the countries' default possibilities with the help of modern techniques of continuous optimization, especially conic quadratic programming. We want to show that the continuous optimization techniques used in data mining are also very successful in financial theory and application. By this paper we contribute to further benefits from model-based methods of applied mathematics in the financial sector. Herewith, we aim to help build up our nations. (C) 2010 Elsevier B.V. All rights reserved.Öğe Mathematical contributions to dynamics and optimization of gene-environment networks(TAYLOR & FRANCIS LTD, 2008) Weber, Gerhard-Wilhelm; Tezel, Aysun; Taylan, Pakize; Soyler, Alper; Cetin, MehmetThis article contributes to a further introduction of continuous optimization in the field of computational biology which is one of the most challenging and emerging areas of science, in addition to foundations presented and the state-of-the-art displayed in [C.A. Floudas and P.M. Pardalos, eds., Optimization in Computational Chemistry and Molecular Biology: Local and Global Approaches, Kluwer Academic Publishers, Boston, 2000]. Based on a summary of earlier works by the coauthors and their colleagues, it refines the model on gene-environment patterns by a problem from generalized semi-infinite programming (GSIP), and characterizes the condition of its structural stability. Furthermore, our paper tries to detect and understand structural frontiers of our methods applied to the recently introduced gene-environment networks and tries to overcome them. Computational biology is interdisciplinary, but it also looks for its mathematical foundations. From data got by DNA microarray experiments, non-linear ordinary differential equations are extracted by the optimization of least-squares errors; then we derive corresponding time-discretized dynamical systems. Using a combinatorial algorithm with polyhedra sequences we can detect the regions of parametric stability, contributing to a testing the goodness of data fitting of the model. To represent and interpret the dynamics, certain matrices, genetic networks and, more generally, gene-environment networks serve. Here, we consider n genes in possible dependence with m special environmental factors and a cumulative one. These networks are subject of discrete mathematical questions, but very large structures, such that we need to simplify them. This is undertaken in a careful optimization with constraints, aiming at a balanced connectedness, incorporates any type of a priori knowledge or request and should be done carefully enough to be robust against disturbation by the environment. In this way, we take into account attacks on the network, knockout phenomena and catastrophies, but also changes in lifestyle and effects of education as far as they can approximately be quantified. We characterize the structural stability of the GSIP problem against perturbations like changes between data series or due to outliers. We give explanations on the numerics and the use of splines. This study is an attempt to demonstrate some beauty and applicabilty of continuous optimization which might together one day give a support in health care, food engineering, biomedicine and -technology, including elements of bioenergy and biomaterials.Öğe A Multi Objective Model for Optimization of a Green Supply Chain Network(Amer Inst Physics, 2010) Paksoy, Turan; Özceylan, Eren; Weber, Gerhard-WilhelmThis study develops a model of a closed-loop supply chain (CLSC) network which starts with the suppliers and recycles with the decomposition centers. As a traditional network design, we consider minimizing the all transportation costs and the raw material purchasing costs. To pay attention for the green impacts, different transportation choices are presented between echelons according to their CO2 emissions. The plants can purchase different raw materials in respect of their recyclable ratios. The focuses of this paper are conducting the minimizing total CO2 emissions. Also we try to encourage the customers to use recyclable materials as an environmental performance viewpoint besides minimizing total costs. A multi objective linear programming model is developed via presenting a numerical example. We close the paper with recommendations for future researches.Öğe MULTI-LEVEL OPTIMIZATION OF AN AUTOMOTIVE CLOSED-LOOP SUPPLY CHAIN NETWORK WITH INTERACTIVE FUZZY PROGRAMMING APPROACHES(VILNIUS GEDIMINAS TECH UNIV, 2018) Yildizbasi, Abdullah; Calik, Ahmet; Paksoy, Turan; Zanjirani Farahani, Reza; Weber, Gerhard-WilhelmClosed-Loop Supply Chain (CLSC) management has attained appreciable attention over the last few years. CLSC management allows companies to manage their recovery and recycling activities of end products. Due to the latest developments in the world, producers are responsible for the collection, refurbishing, repairing and disassembly of end products at the end of their lives. This paper develops a mixed-integer CLSC model that is inspired by the automotive industry. In this model, we consider three Decision Makers (DM): Plant, Dismantler Center and Customer. Each DM has individual objectives and is responsible for only its own objective function under same constraints. In order to tackle the trade-offs among the objectives, we used four different Interactive Fuzzy Programming (IFP) approaches. The applications of the model and solution techniques are investigated in conjectural data. The paper ends with a conclusion and a call for future studies.Öğe Profit oriented supply chain network optimization(SPRINGER, 2013) Paksoy, Turan; Ozceylan, Eren; Weber, Gerhard-WilhelmThis paper proposes a novel mixed integer linear programming model to solve a supply chain network design problem. The proposed model deals with major issues for supply chains; product quality and cost. These issues are usually solved separately, but in this paper, we investigate effects of product quality on supply chain design and transportation flow. A trade-off between raw material quality, its purchasing and reprocessing costs was considered. Assuming decision maker (DM) wishes to work with a supplier which serves a low quality raw material; this raw material should be in need of reprocessing. To avoid the reprocessing costs, a supplier which serves a high quality raw material should be chosen but at this time the DM has to face a high purchasing cost. A supply chain network which consists of multiple suppliers, manufacturers, distribution centers and retailers is tried to be designed to accomplish aforementioned above trade-offs. The paper examines and discusses the relationship between product quality and supply chain design and offers several managerial insights.
