Publications with Fulltext
Permanent URI for this collectionhttps://hdl.handle.net/20.500.14288/6
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Publication Open Access An investigation of time-inconsistency(Informs, 2009) Öncüler, Ayşe; Department of Business Administration; Department of Business Administration; Sayman, Serdar; Faculty Member; Department of Business Administration; College of Administrative Sciences and Economics; 112222Preference between two future outcomes may change over time-a phenomenon labeled as time inconsistency. The term "time inconsistency" is usually used to refer to cases in which a larger-later outcome is preferred over a smaller-sooner one when both are delayed by some time, but then with the passage of time a preference switches to the smaller-sooner outcome. The current paper presents four empirical studies showing that time inconsistency in the other direction is also possible: A person may prefer the smaller-sooner outcome when both options are in the future, but decide to wait for the larger-later one when the smaller option becomes immediately available. We. find that such "reverse time inconsistency" is more likely to be observed when the delays to and between the two outcomes are short (up to a week). We propose that reverse time inconsistency may be associated with a reversed-S shape discount function, and provide evidence that such a discount function captures part of the variation in intertemporal preferences.Publication Open Access Purchasing, production, and sales strategies for a production system with limited capacity, fluctuating sales and purchasing prices(Taylor _ Francis, 2019) N/A; Department of Business Administration; Karabağ, Oktay; Tan, Barış; Resercher; Faculty Member; Department of Business Administration; Graduate School of Sciences and Engineering; College of Administrative Sciences and Economics; N/A; 28600In many industries, the revenue and cost structures of manufacturers are directly affected by the volatility of purchasing and sales prices in the markets. We analyze the purchasing, production, and sales policies for a continuous-review discrete material flow production/inventory system with fluctuating and correlated purchasing and sales prices, exponentially distributed raw material and demand inter-arrival times, and processing time. The sales and purchasing prices are driven by the random environmental changes that evolve according to a discrete state space continuous-time Markov process. We model the system as an infinite-horizon Markov decision process under the average reward criterion and prove that the optimal purchasing, production, and sales strategies are state-dependent threshold policies. We propose a linear programming formulation to compute the optimal threshold levels. We examine the effects of the sales price variation, purchasing price variation, correlation between sales and purchasing prices, customer arrival rate and limited inventory capacities on the system performance measures, through a range of numerical experiments. We also examine under which circumstances the use of the optimal policy notably improves the system profit compared to the use of the buy low and sell high naive policy. We show that using the optimal purchasing, production, and sales policies allow manufacturers to improve their profits when the purchasing and sales prices fluctuate.Publication Open Access The state-dependent M/G/1 queue with orbit(Springer, 2018) Baron, Opher; Economou, Antonis; Department of Industrial Engineering; Manou, Athanasia; Faculty Member; Department of Industrial Engineering; College of EngineeringWe consider a state-dependent single-server queue with orbit. This is a versatile model for the study of service systems, where the server needs a non-negligible time to retrieve waiting customers every time he completes a service. This situation arises typically when the customers are not physically present at a system, but they have a remote access to it, as in a call center station, a communication node, etc. We introduce a probabilistic approach for the performance evaluation of this queueing system, that we refer to as the queueing and Markov chain decomposition approach. Moreover, we discuss the applicability of this approach for the performance evaluation of other non-Markovian service systems with state dependencies.Publication Open Access Capacity planning for effective cohorting of hemodialysis patients during the coronavirus pandemic: a case study(Elsevier, 2023) Bozkır, C.D.C.; Özmemiş, C.; Kurbanzade, A.K.; Balçık, B.; Tuğlular, S.; Department of Business Administration; Güneş, Evrim Didem; Faculty Member; Department of Business Administration; College of Administrative Sciences and Economics; 51391Planning treatments of different types of patients have become challenging in hemodialysis clinics during the COVID-19 pandemic due to increased demands and uncertainties. In this study, we address capacity planning decisions of a hemodialysis clinic, located within a major public hospital in Istanbul, which serves both infected and uninfected patients during the COVID-19 pandemic with limited resources (i.e., dialysis machines). The clinic currently applies a 3-unit cohorting strategy to treat different types of patients (i.e., uninfected, infected, suspected) in separate units and at different times to mitigate the risk of infection spread risk. Accordingly, at the beginning of each week, the clinic needs to allocate the available dialysis machines to each unit that serves different patient cohorts. However, given the uncertainties in the number of different types of patients that will need dialysis each day, it is a challenge to determine which capacity configuration would minimize the overlapping treatment sessions of different cohorts over a week. We represent the uncertainties in the number of patients by a set of scenarios and present a stochastic programming approach to support capacity allocation decisions of the clinic. We present a case study based on the real-world patient data obtained from the hemodialysis clinic to illustrate the effectiveness of the proposed model. We also compare the performance of different cohorting strategies with three and two patient cohorts.Publication Open Access Modeling and analysis of an auction-based logistics market(Elsevier, 2008) Ağralı, Semra; Department of Business Administration; Department of Industrial Engineering; Tan, Barış; Karaesmen, Fikri; Faculty Member; Faculty Member; Department of Business Administration; Department of Industrial Engineering; College of Administrative Sciences and Economics; College of Engineering; 28600; 3579We consider a logistics spot market where the transportation orders from a number of firms are matched with two types of carriers through a reverse auction. In the spot market, local carriers compete with in-transit carriers that have lower costs. In order to analyze the effects of implementing a logistics spot market on these three parties: firms, local carriers, and in-transit carriers and also the effects of various system parameters, we develop a two-stage stochastic model. We first model the auction in a static setting and determine the expected auction price based on the number of carriers engaging in the auction and their cost distributions. We then develop a continuous-time Markov chain model to evaluate the performance of the system in a dynamic setting with random arrivals and possible abandonment of orders and carriers. By combining these two models, we evaluate the performance measures such as the expected auction price, price paid to the carriers, distribution of orders between local and in-transit carriers, and expected number of carriers and orders waiting at the logistics center in the long run. We present analytical and computational results related to the performance of the system and discuss operation of such a logistics spot market in Turkey.Publication Open Access Structural properties of a class of robust inventory and queueing control problems(Wiley, 2018) Department of Industrial Engineering; N/A; Örmeci, Lerzan; Karaesmen, Fikri; Faculty Member; Faculty Member; Department of Industrial Engineering; College of Engineering; Graduate School of Sciences and Engineering; 32863; 3579; N/AIn standard stochastic dynamic programming, the transition probability distributions of the underlying Markov Chains are assumed to be known with certainty. We focus on the case where the transition probabilities or other input data are uncertain. Robust dynamic programming addresses this problem by defining a min-max game between Nature and the controller. Considering examples from inventory and queueing control, we examine the structure of the optimal policy in such robust dynamic programs when event probabilities are uncertain. We identify the cases where certain monotonicity results still hold and the form of the optimal policy is determined by a threshold. We also investigate the marginal value of time and the case of uncertain rewards.Publication Open Access A method for estimating stock-out-based substitution rates by using point-of-sale data(Taylor _ Francis, 2009) Öztürk, Ömer Cem; Department of Business Administration; Tan, Barış; Karabatı, Selçuk; Faculty Member; Faculty Member; Department of Business Administration; College of Administrative Sciences and Economics; 28600; 38819Empirical studies in retailing suggest that stock-out rates are quite high in many product categories. Stock-outs result in demand spillover, or substitution, among items within a product category. Product assortment and inventory management decisions can be improved when the substitution rates are known. In this paper, a method is presented to estimate product substitution rates by using only Point-Of-Sale (POS) data. The approach clusters POS intervals into states where each state corresponds to a specific substitution scenario. Then available POS data for each state is consolidated and the substitution rates are estimated using the consolidated information. An extensive computational analysis of the proposed substitution rate estimation method is provided. The computational analysis and comparisons with an estimation method from the literature show that the proposed estimation method performs satisfactorily with limited information.Publication Open Access Managing portfolio of elective surgical procedures: a multidimensional inverse newsvendor problem(The Institute for Operations Research and the Management Sciences (INFORMS), 2019) Bavafa, Hessam; Leys, Charles M.; Savin, Sergei; Department of Industrial Engineering; Örmeci, Lerzan; Faculty Member; Department of Industrial Engineering; College of Engineering; 32863We consider the problem of allocating daily hospital service capacity among several types of elective surgical procedures in the presence of random numbers of urgent procedures described by arbitrary finite support distributions. Our focus is on the interaction between two major constraining hospital resources: operating room (OR) and recovery bed capacity. In our model, each type of surgical procedure has an associated revenue, stochastic procedure duration, and stochastic length of stay (LOS). We consider arbitrary distributions of procedure and LOS durations and derive a two-moment approximation based on the Central Limit Theorem (CLT) for the total procedure duration and the daily number of occupied beds for a given portfolio of procedures. An important novel element of our model is accounting for correlation among the surgical and patient LOS durations for the procedures performed by the same surgical team. We treat the available OR and recovery bed capacity as nominal, allowing them to be exceeded at a cost. The resulting model is a novel, multidimensional variant of the inverse newsvendor problem, where multiple demand types compete for multiple types of service capacity. We characterize the optimal number of elective procedures for single-specialty hospitals and derive an optimality bound for a "front-end" capacity management approach that focuses exclusively on OR capacity. For a setting with two dominant procedure types, we provide an analytical characterization of the optimal portfolio composition under the condition that the revenue from each procedure is proportional to the expected use of hospital resources. We also derive a general analytical description of the optimal portfolio for an arbitrary number of procedure types. For the general case of an arbitrary number of procedure types in the presence of urgent procedures, we conduct a numerical study using data that we have collected at a medium-sized teaching hospital. Our numerical study illustrates the composition of the optimal portfolios of elective procedures in different practical settings, and it investigates the quality of the CLT-based approximation and the effectiveness of the front-end approach to hospital capacity management.Publication Open Access Front-office multitasking between service encounters and back-office tasks(Elsevier, 2020) Legros, Benjamin; Jouini, Oualid; Koole, Ger; Department of Business Administration; Karaesmen, Zeynep Akşin; Faculty Member; Department of Business Administration; College of Administrative Sciences and Economics; 4534We model the work of a front-line service worker as a queueing system. The server interacts with customers in a multi-stage process with random durations. Some stages require an interaction between server and customer, while other stages are performed by the customer as a self-service task or with the help of another resource. Random arrivals by customers at the beginning and during an encounter create random lengths of idle time in the work of the server (breaks and interludes respectively). The server considers treatment of an infinite amount of back-office tasks, or tasks that do not require interaction with the customer, during these idle times. We consider an optimal control problem for the server's work. The main question we explore is whether to use the interludes in service encounters for treating back-office, when the latter incur switching times. Under certain operating environments, working on back-office during interludes is shown to be valuable. Switching times play a critical role in the optimal control of the server's work, at times leading the server to prefer remaining idle during breaks and interludes, instead of working on back-office, and at others to continue back-office in the presence of waiting customers. The optimal policy for use of the interludes is one with multiple thresholds depending on both the customers queueing for service, and the ones who are in-service. We illustrate that in settings with multiple interludes in an encounter, if at all, the back-office work should be concentrated on fewer, longer and later interludes.Publication Open Access Design of balanced energy savings performance contracts(Taylor _ Francis, 2020) Department of Business Administration; Department of Industrial Engineering; Tan, Barış; Faculty Member; Department of Business Administration; Department of Industrial Engineering; College of Administrative Sciences and Economics; College of Engineering; 28600Energy savings performance contracts between the energy users and the energy service companies (ESCO) are used to finance energy efficiency investments by using the future energy savings that will result from these investments. We present an analytical model to characterise the energy savings performance contracts and discuss how the risks of estimating the energy savings affect the energy user and the service provider. This characterisation allows determination of the contract parameters for a balanced contract with the information about the energy savings that are expected from the planned energy-efficiency investments. Since it is difficult to get the statistical information about the energy savings before investing in an energy-efficiency project, we develop a distribution-free contract that sets the guaranteed energy savings level based on the mean and the standard deviation of the energy savings and the profit-sharing ratio between the ESCO and the energy user. We show that a simple distribution-free balanced contract performs satisfactorily when the distribution of the energy savings is not known and its mean and the standard deviation are estimated with error. Our analytical results show that the energy savings contracts with the right parameters can mitigate the risks related to realisation of the anticipated energy savings.