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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 Metadata only Emergency facility location under random network damage: insights from the Istanbul case(Pergamon-Elsevier Science Ltd, 2015) Department of Industrial Engineering; N/A; Salman, Fatma Sibel; Yücel, Eda; Faculty Member; PhD Student; Department of Industrial Engineering; College of Engineering; Graduate School of Sciences and Engineering; 178838; 235501Damage to infrastructure, especially to highways and roads, adversely affects accessibility to disaster areas. Predicting accessibility to demand points from the supply points by a systematic model would lead to more effective emergency facility location decisions. To this effect, we model the spatial impact of the disaster on network links by random failures with dependency such that failure of a link induces failure of nearby links that are structurally more vulnerable. For each demand point, a set of alternative paths is generated from each potential supply point so that the shortest surviving path will be used for relief transportation after the disaster. The objective is to maximize the expected demand coverage within a specified distance over all possible network realizations. To overcome the computational difficulty caused by extremely large number of possible outcomes, we propose a tabu search heuristic that evaluates candidate solutions over a sample of network scenarios. The scenario generation algorithm that represents the proposed distance and vulnerability based failure model is the main contribution of our study. The tabu search algorithm is applied to Istanbul earthquake preparedness case with a detailed analysis comparing solutions found in no link failure, independent link failure, and dependent link failure cases. The results show that incorporating dependent link failures to the model improves the covered demand percentages significantly.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 Metadata only Mean-variance newsvendor model with random supply and financial hedging(Taylor and Francis Inc, 2015) N/A; Department of Industrial Engineering; Tekin, Müge; Özekici, Süleyman; Master Student; Faculty Member; Department of Industrial Engineering; Graduate School of Sciences and Engineering; College of Engineering; N/A; 32631In this paper, we follow a mean-variance (MV) approach to the newsvendor model. Unlike the risk-neutral newsvendor that is mostly adopted in the literature, the MV newsvendor considers the risks in demand as well as supply. We further consider the case where the randomness in demand and supply is correlated with the financial markets. The MV newsvendor hedges demand and supply risks by investing in a portfolio composed of various financial instruments. The problem therefore includes both the determination of the optimal ordering policy and the selection of the optimal portfolio. Our aim is to maximize the hedged MV objective function. We provide explicit characterizations on the structure of the optimal policy. We also present numerical examples to illustrate the effects of risk-aversion on the optimal order quantity and the effects of financial hedging on risk reduction.Publication Metadata only Newsvendor model with random supply and financial hedging: utility-based approach(Elsevier, 2014) N/A; Department of Industrial Engineering; Department of Industrial Engineering; Karaesmen, Fikri; Özekici, Süleyman; N/A; Faculty Member; Faculty Member; Department of Industrial Engineering; N/A; College of Engineering; College of Engineering; N/A; 3579; 32631This paper takes a utility-based approach to the single-period and single-item newsvendor model. Unlike most models in the literature the newsvendor is not necessarily risk-neutral and chooses the order quantity that maximizes the expected utility of the cash flow at the end of the period. We suppose that there is uncertainty in demand as well as supply. Furthermore, random demand and supply may be correlated with the financial markets. the newsvendor exploits this correlation and manages his risks by investing in a portfolio of financial instruments. the decision problem therefore includes not only the determination of the optimal ordering policy, but also the selection of the optimal portfolio at the same time. We first use a minimum-variance approach to select the portfolio. the analysis results in some interesting and explicit characterizations on the structure of the optimal policy. We also present numerical examples to illustrate the effects of the parameters on the optimal order quantity, and the importance of financial hedging on risk reduction.Publication Open Access Rounding on the standard simplex: regular grids for global optimization(Springer, 2014) Bomze, Immanuel M.; Gollowitzer, Stefan; Department of Industrial Engineering; Yıldırım, Emre Alper; Faculty Member; Department of Industrial Engineering; College of EngineeringGiven a point on the standard simplex, we calculate a proximal point on the regular grid which is closest with respect to any norm in a large class, including all l(p)-norms for p >= 1 . We show that the minimal l(p)-distance to the regular grid on the standard simplex can exceed one, even for very fine mesh sizes in high dimensions. Furthermore, for p = 1, the maximum minimal distance approaches the l(1)-diameter of the standard simplex. We also put our results into perspective with respect to the literature on approximating global optimization problems over the standard simplex by means of the regular grid.Publication Open Access Supervised-learning-based approximation method for multi-server queueing networks under different service disciplines with correlated interarrival and service times(Taylor _ Francis, 2021) Department of Business Administration; N/A; Tan, Barış; Khayyati, Siamak; Faculty Member; Department of Business Administration; College of Administrative Sciences and Economics; Graduate School of Sciences and Engineering; 28600; N/ADeveloping efficient performance evaluation methods is important to design and control complex production systems effectively. We present an approximation method (SLQNA) to predict the performance measures of queueing networks composed of multi-server stations operating under different service disciplines with correlated interarrival and service times with merge, split, and batching blocks separated with infinite capacity buffers. SLQNA yields the mean, coefficient of variation, and first-lag autocorrelation of the inter-departure times and the distribution of the time spent in the block, referred as the cycle time at each block. The method generates the training data by simulating different blocks for different parameters and uses Gaussian Process Regression to predict the inter-departure time and the cycle time distribution characteristics of each block in isolation. The predictions obtained for one block are fed into the next block in the network. The cycle time distributions of the blocks are used to approximate the distribution of the total time spent in the network (total cycle time). This approach eliminates the need to generate new data and train new models for each given network. We present SLQNA as a versatile, accurate, and efficient method to evaluate the cycle time distribution and other performance measures in queueing networks.Publication Metadata only Three-dimensional temperature predictions in machining processes using finite difference method(Elsevier Science Sa, 2009) N/A; Department of Mechanical Engineering; N/A; Ulutan, Durul; Lazoğlu, İsmail; Dinç, Cenk; Master Student; Faculty Member; Master Student; Department of Mechanical Engineering; Graduate School of Sciences and Engineering; College of Engineering; Graduate School of Sciences and Engineering; 311604; 179391; N/AThe purpose of this study is to determine the three-dimensional temperature fields on the chip, tool and workpiece during machining, which is one of the most important characteristic of machining processes; since the fields can affect other properties such as residual stresses and tool wear, and thus tool life and fatigue life of finished parts. The finite difference method (FDM)-based model proposed in this paper offers very rapid and reasonably accurate solutions. Finite difference-based simulation results are validated with infrared thermal measurements which are determined from the machining of AISI 1050 and AISI H13 materials under various cutting conditions.