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Publication Open Access A hierarchical solution approach for a multicommodity distribution problem under a special cost structure(Elsevier, 2012) Koca, Esra; Department of Industrial Engineering; Yıldırım, Emre Alper; Faculty Member; Department of Industrial Engineering; College of EngineeringMotivated by the spare parts distribution system of a major automotive manufacturer in Turkey, we consider a multicommodity distribution problem from a central depot to a number of geographically dispersed demand points. The distribution of the items is carried out by a set of identical vehicles. The demand of each demand point can be satisfied by several vehicles and a single vehicle is allowed to serve multiple demand points. For a given vehicle, the cost structure is dictated by the farthest demand point from the depot among all demand points served by that vehicle. The objective is to satisfy the demand of each demand point with the minimum total distribution cost. We present a novel integer linear programming formulation of the problem as a variant of the network design problem. The resulting optimization problem becomes computationally infeasible for real-life problems due to the large number of integer variables. In an attempt to circumvent this disadvantage of using the direct formulation especially for larger problems, we propose a Hierarchical Approach that is aimed at solving the problem in two stages using partial demand aggregation followed by a disaggregation scheme. We study the properties of the solution returned by the Hierarchical Approach. We perform computational studies on a data set adapted from a major automotive manufacturer in Turkey. Our results reveal that the Hierarchical Approach significantly outperforms the direct formulation approach in terms of both the running time and the quality of the resulting solution especially on large instances.Publication Open Access A model-based heuristic to the min max K-arc routing for connectivity problem(Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2014) Akbari, Vahid; Department of Industrial Engineering; Salman, Fatma Sibel; Faculty Member; Department of Industrial Engineering; College of Engineering; 178838We consider the post-disaster road clearing problem with the goal of restoring network connectivity in shortest time. Given a set of blocked edges in the road network, teams positioned at depot nodes are dispatched to open a subset of them that reconnects the network. After a team finishes working on an edge, others can traverse it. The problem is to find coordinated routes for the teams. We generate a feasible solution using a constructive heuristic algorithm after solving a relaxed mixed integer program. In almost 70 percent of the instances generated both randomly and from Istanbul data, the relaxation solution turned out to be feasible, i.e. optimal for the original problem.Publication Open Access A new identification method of specific cutting coefficients for ball end milling(Elsevier, 2014) Department of Mechanical Engineering; Khavidaki, Sayed Ehsan Layegh; Lazoğlu, İsmail; Faculty Member; Department of Mechanical Engineering; Manufacturing and Automation Research Center (MARC); Graduate School of Sciences and Engineering; College of Engineering; N/A; 179391The paper presents a new and accurate strategy for estimation of cutting coefficients for ball-end milling of free form surfaces in 3- and 5-axis operations. Since the cutting coefficients are not constant along the tool axis in the ball part of the cutter, the tool is considered by dividing the ball region into thin disks. In order to find the contribution of each disk to resultant cutting force, an experimental setup is designed to cut the workpiece while only that disk is in engaged with the workpiece. It is shown that this method is more efficient than common methods of mechanistic identification of cutting constants that are available in literature. The derivations are improved by considering the helix angle and cutting edge length to enhance the accuracy of the estimated cutting coefficients. Validation of the proposed strategy is demonstrated experimentally by simulation of cutting forces and comparing the results with conventional methods of identification of cutting coefficients that have been proposed in the literature. (C) 2014 Elsevier B.V.Publication Restricted An adaptive large neighborhood search algorithm for selective and periodic inventory routing problem(Koç University, 2013) Tüncel, Özge; Salman, Fatma Sibel; 0000-0001-6833-2552; Koç University Graduate School of Sciences and Engineering; Industrial Engineering; 178838Publication Restricted Energy network optimization of an oil refinery(Koç University, 2017) Mete, Elif; Türkay, Metin; 0000-0003-4769-6714; Koç University Graduate School of Sciences and Engineering; Industrial Engineering; 24956Publication Open Access Integrating gene set analysis and nonlinear predictive modeling of disease phenotypes using a Bayesian multitask formulation(BioMed Central, 2016) Department of Industrial Engineering; Gönen, Mehmet; Faculty Member; Department of Industrial Engineering; College of Engineering; 237468Identifying molecular signatures of disease phenotypes is studied using two mainstream approaches: (i) Predictive modeling methods such as linear classification and regression algorithms are used to find signatures predictive of phenotypes from genomic data, which may not be robust due to limited sample size or highly correlated nature of genomic data. (ii) Gene set analysis methods are used to find gene sets on which phenotypes are linearly dependent by bringing prior biological knowledge into the analysis, which may not capture more complex nonlinear dependencies. Thus, formulating an integrated model of gene set analysis and nonlinear predictive modeling is of great practical importance. In this study, we propose a Bayesian binary classification framework to integrate gene set analysis and nonlinear predictive modeling. We then generalize this formulation to multitask learning setting to model multiple related datasets conjointly. Our main novelty is the probabilistic nonlinear formulation that enables us to robustly capture nonlinear dependencies between genomic data and phenotype even with small sample sizes. We demonstrate the performance of our algorithms using repeated random subsampling validation experiments on two cancer and two tuberculosis datasets by predicting important disease phenotypes from genome-wide gene expression data. We are able to obtain comparable or even better predictive performance than a baseline Bayesian nonlinear algorithm and to identify sparse sets of relevant genes and gene sets on all datasets. We also show that our multitask learning formulation enables us to further improve the generalization performance and to better understand biological processes behind disease phenotypes.Publication Open Access Joint gateway selection, transmission slot assignment, routing and power control for wireless mesh networks(Elsevier, 2013) Gökbayrak, Kağan; Department of Industrial Engineering; Yıldırım, Emre Alper; Faculty Member; Department of Industrial Engineering; College of EngineeringWireless mesh networks (WMNs) provide cost effective solutions for setting up a communications network over a certain geographic area. In this paper, we study strategic problems of WMNs such as selecting the gateway nodes along with several operational problems such as routing, power control, and transmission slot assignment. Under the assumptions of the physical interference model and the tree-based routing restriction for traffic flow, a mixed integer linear programming (MILP) formulation is presented, in which the objective is to maximize the minimum service level provided at the nodes. A set of valid inequalities is derived and added to the model in an attempt to improve the solution quality. Since the MILP formulation becomes computationally infeasible for larger instances, we propose a heuristic method that is aimed at solving the problem in two stages. In the first stage, we devise a simple MILP problem that is concerned only with the selection of gateway nodes. In the second stage, the MILP problem in the original formulation is solved by fixing the gateway nodes from the first stage. Computational experiments are provided to evaluate the proposed models and the heuristic method.Publication Restricted Logistics planning for restoration of network connectivity after a disaster(Koç University, 2013) Kibar, Ayşe Nur; Salman, Fatma Sibel; 0000-0001-6833-2552; Koç University Graduate School of Sciences and Engineering; Industrial Engineering; 178838Publication Open Access Machining forces and tool deflections in micro milling(Elsevier, 2013) Department of Mechanical Engineering; Mamedov, Ali; Khavidaki, Sayed Ehsan Layegh; Lazoğlu, İsmail; Researcher; Faculty Member; Department of Mechanical Engineering; Manufacturing and Automation Research Center (MARC); Graduate School of Sciences and Engineering; College of Engineering; N/A; N/A; 179391The analysis of cutting forces plays an important role for investigation of mechanics and dynamics of cutting process. The importance of force analysis is due to its major role in surface quality of machined parts. Presented force model calculates instantaneous chip thickness by considering trajectory of the tool tip while tool rotates and moves ahead continuously. The model also takes plowing force component into consideration relating it to elastic recovery based on interference volume between tool and workpiece. Based on the mathematical model, distribution of the force acting on the tool is calculated. It is known that this force will create deflection of the tool during cutting, which will result in imperfections of the final part. From this point of view, it is important to predict tool deflections in order to control the cutting process and to avoid failure of the tool. Both force and deflection models are validated on Aerospace Aluminum Alloy (Al-7050), through micro end milling experiments for a wide range of cutting conditions using micro dynamometer and laser displacement sensors. (C) 2013 The Authors. Published by Elsevier B.V.Publication Restricted Market clearing models in European day ahead electricity models(Koç University, 2019) Şahin, Nermin Elif Kurt; Yıldırım, Emre Alper; Koç University Graduate School of Sciences and Engineering; Industrial Engineering and Operations Management