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Permanent URI for this collectionhttps://hdl.handle.net/20.500.14288/3
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Publication Metadata only Energy-efficient production control of a make-to-stock system with buffer- and time-based policies(Taylor and Francis Ltd., 2023) Karabağ, Oktay; Khayyati, Siamak; Department of Business Administration; Tan, Barış; Department of Business Administration; College of Administrative Sciences and EconomicsIncreasing energy efficiency in manufacturing has significant environmental and cost benefits. Turning on or off a machine dynamically while considering the production rate requirements can offer substantial energy savings. In this work, we examine the optimal policies to control production and turn on and off a machine that operates in working, idle, off, and warmup modes for the case where demand inter-arrival, production, and warmup times have phase-type distributions. The optimal control problem that minimises the expected costs associated with the energy usage in different energy modes and the inventory and backlog costs is solved using a linear program associated with the underlying Markov Decision Process. We also present a matrix-geometric method to evaluate the steady-state performance of the system under a given threshold control policy. We show that when the inter-arrival time distribution is not exponential, the optimal control policy depends on both the current phase of the inter-arrival time and inventory position. The phase-dependent policy implemented by estimating the current phase based on the time elapsed since the last arrival yields a buffer- and time-based policy to control the energy mode and production. We show that policies that only use the inventory position information can be effective if the control parameters are chosen appropriately. However, the control policies that use both the inventory and time information further improve the performance.Publication Metadata only The digital twin synchronization problem: framework, formulations, and analysis(Taylor & Francis Inc, 2023) Matta, Andrea; Department of Business Administration; Tan, Barış; Department of Business Administration; College of Administrative Sciences and EconomicsAs the adoption of digital twins increases steadily, it is necessary to determine how to operate them most effectively and efficiently. In this article, the digital twin synchronization problem is introduced and defined formally. Frequent synchronizations would increase cost and data traffic congestion, whereas infrequent synchronizations would increase the bias of the predictions and yield wrong decisions. This work defines the synchronization problem variants in different contexts. To discuss the problem and its solution, the problem of determining when to synchronize an unreliable production system with its digital twin to minimize the average synchronization and bias costs is formulated and analyzed analytically. The state-independent, state-dependent, and full-information solutions have been determined by using a stochastic model of the system. Solving the synchronization problem using simulation is discussed, and an approximate policy is proposed. Our results show that the performance of the state-dependent policy is close to the optimal solution that can be obtained with full information and significantly better than the performance of the state-independent policy. Furthermore, the approximate periodic state-dependent policy yields near-optimal results. To operate digital twins more effectively, the digital twin synchronization problem must be considered and solved to determine the optimal synchronization policy.Publication Metadata only Continuous-flow simulation of manufacturing systems with assembly/disassembly machines, multiple loops and general layout(Elsevier Sci Ltd, 2023) Scrivano, Salvatore; Tolio, Tullio; Department of Business Administration; Tan, Barış; Department of Business Administration; College of Administrative Sciences and EconomicsPerformance evaluation methods are important to design and control manufacturing systems. Approximate analytical methods are fast, but they may be limited by the restrictive assumptions on the system. On the contrary, simulation has not specific limitations in its applicability, but the time to model and analyse a manufacturing system can increase as the level of detail addressed by the model increases. The main contribution of this study is presenting a computationally efficient methodology to simulate single-part continuous-flow manufacturing systems with assembly/disassembly machines, multiple loops, general layout and general inter-event time distributions. By using graph theory, a new method is presented to identify the machines causing slowdown, blocking and starvation in a general layout and determine the time before the occurrence of a state transition for each machine and the time before the fulfilment or depletion of each buffer. By advancing the time clock to the next event-time accordingly, the number of discrete events needed to be simulated is decreased compared to a discrete-event simulation with discrete flow of parts. As a result, the proposed method is on average 15 times faster than DES methods in the analysis of discrete-flow systems, and 110 times faster on average in the analysis of continuous-flow systems. The low computational time of the proposed method allows to simulate systems under general assumptions and in a very short time.Publication Metadata only Dynamic assignment of flexible service resources(Wiley, 2010) Balakrishnan, Anant; Xu, Susan H.; Department of Business Administration; Akçay, Yalçın; Faculty Member; Department of Business Administration; College of Administrative Sciences and Economics; 51400Resource flexibility is an important tool for firms to better match capacity with demand so as to increase revenues and improve service levels. However, in service contexts that require dynamically deciding whether to accept incoming jobs and what resource to assign to each accepted job, harnessing the benefits of flexibility requires using effective methods for making these operational decisions. Motivated by the resource deployment decisions facing a professional service firm in the workplace training industry, we address the dynamic job acceptance and resource assignment problem for systems with general resource flexibility structure, i.e., with multiple resource types that can each perform different overlapping subsets of job types. We first show that, for systems containing specialized resources for individual job types and a versatile resource type that can perform all job types, the exact policy uses a threshold rule. With more general flexibility structures, since the associated stochastic dynamic program is intractable, we develop and test three optimization-based approximate policies. Our extensive computational tests show that one of the methods, which we call the Bottleneck Capacity Reservation policy, is remarkably effective in generating near-optimal solutions over a wide range of problem scenarios. We also consider a model variant that requires dynamic job acceptance decisions but permits deferring resource assignment decisions until the end of the horizon. For this model, we discuss an adaptation of our approximate policy, establish the effectiveness of this policy, and assess the value of postponing assignment decisions.Publication Metadata only Dynamic churn prediction framework with more effective use of rare event data: the case of private banking(Pergamon-Elsevier Science Ltd, 2014) Department of Business Administration; N/A; Ali, Özden Gür; Arıtürk, Umut; Faculty Member; PhD Student; Department of Business Administration; College of Administrative Sciences and Economics; Graduate School of Business; 57780; N/ACustomer churn prediction literature has been limited to modeling churn in the next (feasible) time period. On the other hand, lead time specific churn predictions can help businesses to allocate retention efforts across time, as well as customers, and identify early triggers and indicators of customer churn. We propose a dynamic churn prediction framework for generating training data from customer records, and leverage it for predicting customer churn within multiple horizons using standard classifiers. Further, we empirically evaluate the proposed approach in a case study about private banking customers in a European bank. The proposed framework includes customer observations from different time periods, and thus addresses the absolute rarity issue that is relevant for the most valuable customer segment of many companies. It also increases the sampling density in the training data and allows the models to generalize across behaviors in different time periods while incorporating the impact of the environmental drivers. As a result, this framework significantly increases the prediction accuracy across prediction horizons compared to the standard approach of one observation per customer; even when the standard approach is modified with oversampling to balance the data, or lags of customer behavior features are added as additional predictors. The proposed approach to dynamic churn prediction involves a set of independently trained horizon-specific binary classifiers that use the proposed dataset generation framework. In the absence of predictive dynamic churn models, we had to benchmark survival analysis which is used predominantly as a descriptive tool. The proposed method outperforms survival analysis in terms of predictive accuracy for all lead times, with a much lower variability. Further, unlike Cox regression, it provides horizon specific ranking of customers in terms of churn probability which allows allocation of retention efforts across customers and time periods. (C) 2014 Elsevier Ltd. All rights reserved.Publication Metadata only Revenue management for intermodal transportation: the role of dynamic forecasting(Wiley, 2016) Luo, Ting; Gao, Long; Department of Business Administration; Akçay, Yalçın; Faculty Member; Department of Business Administration; College of Administrative Sciences and Economics; 51400We study a joint capacity leasing and demand acceptance problem in intermodal transportation. The model features multiple sources of evolving supply and demand, and endogenizes the interplay of three leversforecasting, leasing, and demand acceptance. We characterize the optimal policy, and show how dynamic forecasting coordinates leasing and acceptance. We find (i) the value of dynamic forecasting depends critically on scarcity, stochasticity, and volatility; (ii)traditional mean-value equivalence approach performs poorly in volatile intermodal context; (iii) mean-value-based forecast may outperform stationary distribution-based forecast. Our work enriches revenue management models and applications. It advances our understanding on when and how to use dynamic forecasting in intermodal revenue management.Publication Metadata only Modeling and analysis of a cooperative service network(Pergamon-Elsevier Science Ltd, 2021) N/A; N/A; Department of Business Administration; Hosseini, Behnaz; Tan, Barış; PhD Student; Faculty Member; Department of Business Administration; Graduate School of Sciences and Engineering; College of Administrative Sciences and Economics; N/A; 28600With the advances in technology and changes in customers' attitude towards different service delivery formats, it is important for the service providers to deliver online services in addition to the traditional face-to-face services. In the cooperative service network presented in this study, service providers cooperate to serve online service requests received by the network in addition to their own customers. Designing and managing the cooperative network effectively increase the utilization of the involved servers, provide an adequate service for the external customers, and increase the profit for both the network and service providers. From the operational perspective, the number and utilization of the members to be included in the network and the price that will be paid to each member for a directed request are the main design questions. In order to answer these questions, we present a stochastic model that captures the dynamics of customer arrivals, assignment, and admission control. To establish this model, we first derive the solution of the dynamic admission control problem for the servers who decide how to admit their own customers and the external online customers using a Markov decision process. We then analyze the operation of the whole network with the servers who use the optimal admission control policy and obtain the system performance measures depending on the members' operational parameters. These results are used to determine the optimal number of servers in the network and the service price to be paid to the participating servers in order to maximize the obtained profit. We show that a cooperative service network is an effective way of utilizing the idle capacity of the servers while providing an adequate service level for the external online customers and increasing the profit for both the network and service providers.Publication Metadata only Whose innovation performance benefits more from external networks: Entrepreneurial or conservative firms?(WILEY, 2016) Baker, William E.; Grinstein, Amir; Department of Business Administration; Harmancıoğlu, Nükhet; Faculty Member; Department of Business Administration; College of Administrative Sciences and Economics; 123423The primary contribution of this research is positing and empirically supporting the proposition that learning through external networks disproportionately benefits conservative, risk-averse firms. The construct, entrepreneurial orientation (EO), is used to discriminate conservative, risk-averse firms from proactive, risk-seeking firms. Organizational learning theory and social capital theory are employed to support our hypotheses. Based on a study of 1978 U.S. firms, the paper suggests that the utilization of external networks (i.e., the process of learning from information, perspectives, and insights embedded in external networks) may act as a primary driver for innovation for those firms that are either not inclined and/or do not have the capabilities to adopt entrepreneurial culture. Specifically, weak EO firms' innovation performance benefits from utilizing external networks more than strong EO firms'. This research also tests for the moderating role of firm size and finds that the negative moderating effect of EO on the external network utilization–innovation performance relationship is more pronounced in small and medium sized enterprises (SMEs) than large firms.Publication Metadata only Flow-line scheduling problem with controllable processing times(Taylor & Francis, 1997) Kouvelis, P.; Department of Business Administration; Karabatı, Selçuk; Faculty Member; Department of Business Administration; College of Administrative Sciences and Economics; 38819In this paper we address the simultaneous scheduling and optimal-processing-times selection problem in a multi-product deterministic flow line operated under a cyclic scheduling approach. The selection of processing times plays an important role in achieving the desired production rate with the least possible operating cost. We first formulate the important subproblem of optimal-processing-times selection for different objectives, when the sequence of jobs is fixed, and then develop an efficient solution procedure for it. The fast solution of the fixed sequence problem is necessary for the development of efficient approximate solution procedures for the simultaneous scheduling and optimal-processing-times problem. A computational study on the effectiveness of the proposed solution procedure is presented. For the solution of the simultaneous scheduling and optimal-processing-times problem we suggest an iterative solution procedure, and report our computational experience with this procedure. For the solution of large problems we present a genetic algorithm. The effectiveness of the algorithm is demonstrated through computational results and by evaluating the performance of the obtained solutions against lower bounds that we developed for the problem.Publication Metadata only It won't fit! for innovative products, sometimes that's for the best(Wiley, 2015) Stanko, Michael A.; Molina-Castillo, Francisco-Jose; Department of Business Administration; Harmancıoğlu, Nükhet; Faculty Member; Department of Business Administration; College of Administrative Sciences and Economics; 123423The degree of overlap (i.e., fit) between product development organizations' resources and the product development projects pursued has powerful performance implications. Drawing on organizational learning theory and the resource-based view, this research conceptualizes and empirically tests the interrelationships between the levels of fit, innovativeness, speed to market, and financial new product performance. After reviewing the research literature relevant to resource fit and new product performance, the level of innovativeness is posited to be an important moderating and mediating factor, which is validated by analysis of data gathered from 279 product developing firms. Technological fit has a negative direct effect on both technological and market innovativeness, while the use of existing marketing resources (i.e., a high degree of marketing fit) positively impacts technological innovativeness. This suggests, consistent with findings from market orientation research, that a deep, long-held customer understanding can promote technological innovativeness. The moderating hypotheses proposed are also well supported: First, a high degree of marketing fit has a more positive impact on performance for market innovative products (e.g., products which address a new target market or use a nontraditional channel for the firm). Drawing on a deep customer understanding is more critical to performance for market innovative products. Conversely, the benefits of marketing fit are limited where market innovativeness is lacking. Interestingly, the counterpart moderating role of technological innovativeness on technological fit's performance effect is not significant; the level of technological innovativeness does not significantly impact the performance impact of technological fit. There are also significant moderating effects across dimensions. Our results show that the financial benefit of using existing marketing resources is lessened for technologically innovative products. Technological innovations necessitate drastic adaptation of marketing resources (i.e., channel and brand); firms drawing only on existing marketing resources for a technologically innovative new product will incur reduced profit. Similarly, the positive implications of using existing technological resources are limited for products which are highly market innovative. Generally, resource fit is seen to have an (oft-overlooked) dark side in product development, though several of our findings suggest that marketing resources are more flexible than are technological resources.