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Publication Metadata only A procedure to find discrete representations of the efficient set with specified coverage errors(Inst Operations Research Management Sciences, 2003) Department of Business Administration; Sayın, Serpil; Faculty Member; Department of Business Administration; College of Administrative Sciences and Economics; 6755An important issue in multiple objective mathematical programming is finding discrete representations of the efficient set. Because discrete points can be directly studied by a decision maker, a discrete representation can serve as the solution to the multiple objective problem at hand. However, the discrete representation must be of acceptable quality to ensure that a most-preferred solution identified by a decision maker is of acceptable quality. Recently, attributes for measuring the quality of discrete representations have been proposed. Although discrete representations can be obtained in many different ways, and their quality evaluated afterwards, the ultimate goal should be to find such representations so as to conform to specified quality standards. We present a method that can find discrete representations of the efficient set according to a specified level of quality. The procedure is based on mathematical programming tools and can be implemented relatively easily when the domain of interest is a polyhedron. The nonconvexity of the efficient set is dealt with through a coordinated decomposition approach. We conduct computational experiments and report results.Publication Metadata only A variable neighborhood search for minimizing total weighted tardiness with sequence dependent setup times on a single machine(Pergamon-Elsevier Science Ltd, 2012) N/A; N/A; Department of Industrial Engineering; Kirlik, Gökhan; Oğuz, Ceyda; PhD Student; Faculty Member; Department of Industrial Engineering; Graduate School of Sciences and Engineering; College of Engineering; N/A; 6033This paper deals with the single machine scheduling problem to minimize the total weighted tardiness in the presence of sequence dependent setup. Firstly, a mathematical model is given to describe the problem formally. Since the problem is NP-hard, a general variable neighborhood search (GVNS) heuristic is proposed to solve it. Initial solution for the GVNS algorithm is obtained by using a constructive heuristic that is widely used in the literature for the problem. The proposed algorithm is tested on 120 benchmark instances. The results show that 37 out of 120 best known solutions in the literature are improved while 64 instances are solved equally. Next, the GVNS algorithm is applied to single machine scheduling problem with sequence dependent setup times to minimize the total tardiness problem without changing any implementation issues and the parameters of the GVNS algorithm. For this problem, 64 test instances are solved varying from small to large sizes. Among these 64 instances, 35 instances are solved to the optimality, 16 instances' best-known results are improved, and 6 instances are solved equally compared to the best-known results. Hence, it can be concluded that the GVNS algorithm is an effective, efficient and a robust algorithm for minimizing tardiness on a single machine in the presence of setup times.Publication Metadata only Assessing the reliability and the expected performance of a network under disaster risk(Springer, 2011) Günneç, Dilek; Department of Industrial Engineering; Salman, Fatma Sibel; Faculty Member; Department of Industrial Engineering; College of Engineering; 178838In a disaster situation, functionality of an infrastructure network is critical for effective emergency response. We evaluate several probabilistic measures of connectivity and expected travel time/distance between critical origin-destination pairs to assess the functionality of a given transportation network in case of a disaster. The input data include the most likely disaster scenarios as well as the probability that each link of the network fails under each scenario. Unlike most studies that assume independent link failures, we model dependency among link failures and propose a novel dependency model that incorporates the impact of the disaster on the network and at the same time yields tractable cases for the computation of the probabilistic measures. We develop algorithms for the computation of the measures and utilize a Monte Carlo simulation algorithm for the intractable cases. We present a case study of the Istanbul highway system under earthquake risk, and compare different dependency structures computationally.Publication Metadata only Asymptotic variance rate of the output in production lines with finite buffers(Baltzer Sci Publ Bv, 2000) Department of Business Administration; Tan, Barış; Faculty Member; Department of Business Administration; College of Administrative Sciences and Economics; 28600Production systems that can be modeled as discrete time Markov chains are considered. A state-space-based method is developed to determine the variance of the number of parts produced per unit time in the long run. This quantity is also referred to as the asymptotic variance rate. The block tridiagonal structure of the probability matrix of a general two-station production line with a finite buffer is exploited and a recursive method based on matrix geometric solution is used to determine the asymptotic variance rate of the output. This new method is computationally very efficient and yields a thousand-fold improvement in the number of operations over the existing methods. Numerical experiments that examine the effects of system parameters on the variability of the performance of a production line are presented. The computational efficiency of the method is also investigated. Application of this method to longer lines is discussed and exact results for a three-station production line with finite interstation buffers are presented. A thorough review of the pertinent literature is also given.Publication Metadata only Berth and quay crane allocation: a moldable task scheduling model(Taylor & Francis, 2011) Blazewicz, Jacek; Cheng, T. C. E.; Machowiak, Maciej; Department of Industrial Engineering; Oğuz, Ceyda; Faculty Member; Department of Industrial Engineering; College of Engineering; 6033We study the problem of allocating berths to incoming ships and assigning the necessary quay cranes to the ships at a port container terminal. We formulate the problem as the moldable task scheduling problem by considering the tasks as ships and processors as quay cranes assigned to the ships based on the observation that the berthing duration of a ship depends on the number of quay cranes allocated to it. In the model, the processing speed of a task is considered to be a non-linear function of the number of processors allocated to it. We present a suboptimal algorithm that obtains a feasible solution to the discrete version of the problem from the continuous version, that is, where the tasks may require fractional quantities of the resources. We conducted computational experiments to evaluate the performance of the algorithm. The computational results show that the average behaviour of the algorithm is very good.Publication Metadata only Cross-selling investment products with a win-win perspective in portfolio optimization(Informs, 2017) Özçelik, M. Hamdi; Department of Business Administration; Department of Business Administration; Department of Business Administration; N/A; Ali, Özden Gür; Akçay, Yalçın; Sayman, Serdar; Yılmaz, Emrah; Faculty Member; Faculty Member; Faculty Member; PhD Student; Department of Business Administration; College of Administrative Sciences and Economics; College of Administrative Sciences and Economics; College of Administrative Sciences and Economics; Graduate School of Business; 57780; 51400; 112222; N/AWe propose a novel approach to cross-selling investment products that considers both the customers' and the bank's interests. Our goal is to improve the risk-return profile of the customer's portfolio and the bank's profitability concurrently, essentially creating a win-win situation, while deepening the relationship with an acceptable product. Our cross-selling approach takes the customer's status quo bias into account by starting from the existing customer portfolio, rather than forming an efficient portfolio from scratch. We estimate a customer's probability of accepting a product offer with a predictive model using readily available data. Then, we model the investment product cross-selling problem as a nonlinear mixed-integer program that maximizes a customer's expected return from the proposed portfolio, while ensuring that the bank's profitability improves by a certain factor. We implemented our methodology at the private banking division of Yapi Kredi, the fourth-largest private bank in Turkey. Empirical results from this application illustrate that (1) a traditional mean-variance portfolio optimization approach does not increase portfolio returns and reduces overall bank profits, (2) a standard cross-selling approach increases bank profits at the expense of the customers' portfolio returns, and (3) our win-win approach increases the expected portfolio returns of customers without increasing their variances, while simultaneously improving bank profits substantially.Publication Metadata only Driver moderator method for retail sales prediction(World Scientific Publ Co Pte Ltd, 2013) Department of Business Administration; Ali, Özden Gür; Faculty Member; Department of Business Administration; College of Administrative Sciences and Economics; 57780We introduce a new method for stock keeping unit (SKU)-store level sales prediction in the presence of promotions to support order quantity and promotion planning decisions for retail managers. The method leverages the marketing literature to generate features, and data mining techniques to train a model that provides accurate sales predictions for existing and new SKUs, as well as consistent, actionable insights into category, store and promotion dynamics. The proposed "Driver Moderator" method uses basic SKU-store information and historical sales and promotion data to generate many features. It simultaneously selects few relevant features and estimates their parameters by using an L1-norm regularized epsilon insensitive regression that is formulated to pool information across SKUs and stores. Evaluations on two grocery store databases from Turkey and the USA show that out-of-sample predictions for existing and new SKUs are as good as, or more accurate than benchmark methods. Using the method's predictions for inventory decisions doubles the inventory turn ratio versus using individual regressions by lowering lost sales and inventory levels at the same time.Publication Metadata only Effects of system parameters on the optimal cost and policy in a class of multidimensional queueing control problems(The Institute for Operations Research and the Management Sciences (INFORMS), 2018) Vercraene, Samuel; Gayon, Jean-Philippe; Department of Industrial Engineering; Karaesmen, Fikri; Faculty Member; Department of Industrial Engineering; College of Engineering; 3579We consider a class of Markov Decision Processes frequently employed to model queueing and inventory control problems. For these problems, we explore how changes in different system input parameters (transition rates, costs, discount rates etc.) affect the optimal cost and the optimal policy when the state space of the problem is multidimensional. To address a large class of problems, we introduce two generic dynamic programming operators to model different types of controlled events. For these operators, we derive sufficient conditions to propagate monotonicity and supermodularity properties of the value function. These properties allow to predict how changes in system input parameters affect the optimal cost and policy. Finally, we explore the case when several parameters are changed at the same time.Publication Metadata only Greedy algorithm for the general multidimensional knapsack problem(Springer, 2007) Li, Haijun; Xu, Susan H.; Department of Business Administration; Akçay, Yalçın; Faculty Member; Department of Business Administration; College of Administrative Sciences and Economics; 51400In this paper, we propose a new greedy-like heuristic method, which is primarily intended for the general MDKP, but proves itself effective also for the 0-1 MDKP. Our heuristic differs from the existing greedy-like heuristics in two aspects. First, existing heuristics rely on each item's aggregate consumption of resources to make item selection decisions, whereas our heuristic uses the effective capacity, defined as the maximum number of copies of an item that can be accepted if the entire knapsack were to be used for that item alone, as the criterion to make item selection decisions. Second, other methods increment the value of each decision variable only by one unit, whereas our heuristic adds decision variables to the solution in batches and consequently improves computational efficiency significantly for large-scale problems. We demonstrate that the new heuristic significantly improves computational efficiency of the existing methods and generates robust and near-optimal solutions. The new heuristic proves especially efficient for high dimensional knapsack problems with small-to-moderate numbers of decision variables, usually considered as "hard" MDKP and no computationally efficient heuristic is available to treat such problems.Publication Metadata only Health network mergers and hospital re-planning(Taylor & Francis, 2010) Yaman, H.; Department of Business Administration; Güneş, Evrim Didem; Faculty Member; Department of Business Administration; College of Administrative Sciences and Economics; 51391This paper presents an integer programming formulation for the hospital re-planning problem which arises after hospital network mergers. The model finds the best re-allocation of resources among hospitals, the assignment of patients to hospitals and the service portfolio to minimize the system costs subject to quality and capacity constraints. An application in the Turkish hospital networks case is illustrated to show the implications of consolidation of health insurance funds on resource allocations and flow of patients in the system. Journal of the Operational Research Society (2010) 61, 275-283. doi: 10.1057/jors.2008.165 Published online 11 February 2009
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