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Permanent URI for this collectionhttps://hdl.handle.net/20.500.14288/3
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Publication Metadata only Managing home health-care services with dynamic arrivals during a public health emergency(IEEE-Inst Electrical Electronics Engineers Inc, 2024) Araz, Özgür M.; Department of Industrial Engineering; Çınar, Ahmet; Salman, Fatma Sibel; Parçaoğlu, Mert; Department of Industrial Engineering; ; Graduate School of Sciences and Engineering; College of Engineering;We consider a public health emergency, during which a high number of patients and their varying health conditions necessitate prioritizing patients receiving home health care. Moreover, the dynamic emergence of patients needing urgent care during the day should be handled by rescheduling these patients. In this article, we present a reoptimization framework for this dynamic problem to periodically determine which patients will be visited in which order on each day to maximize the total priority of visited patients and to minimize the overtime for the health-care provider. This optimization framework also aims to minimize total routing time. A mixed-integer programming (MIP) model is formulated and solved at predetermined reoptimization times, to assure that urgent patients are visited within the current day, while visits of others may be postponed, if overtime is not desired or limited. The effectiveness of a schedule is evaluated with respect to several performance metrics, such as the number of patients whose visits are postponed to the next day, waiting time of urgent patients, and required overtime. The MIP-based approach is compared to two practical heuristics that achieve satisfactory performance under a nervous service system by excelling in different criteria. The MIP-based reoptimization approach is demonstrated for a case during the COVID-19 pandemic. We contribute to the home health-care literature by managing dynamic/urgent patient arrivals under a multiperiod setting with prioritized patients, where we optimize different rescheduling objectives via three alternative reoptimization approaches. © 1988-2012 IEEE.Publication Metadata only Incorporating patients’ appointment date preferences into decision-making: a simulation and optimization study(Elsevier Ltd, 2024) Ünsal, Özgür; Üster, Halit; Department of Industrial Engineering; Oğuz, Ceyda; Department of Industrial Engineering; College of EngineeringA recent trend in health care is to give patients more flexibility by taking their preferences into account. While this patient-centered approach adds further complexity to the management of operations, it also generates new opportunities for potential improvements in the system. In this study, we show that such an improvement can be obtained via appointment scheduling (AS) systems which are the critical component of any health care delivery system as they can easily be a source of dissatisfaction for the patients as well as for the providers. Accordingly, we propose a novel patient-oriented AS strategy that utilizes patients’ appointment date preferences. The main idea of the strategy is to accumulate patients’ preferences for some amount of time before deciding on their appointments via mathematical optimization, rather than traditional first-call first-booked strategy in which patients are appointed at the time they call. By this way, we aim to exploit the advantage of giving patients preferences to improve the system performance. To examine the proposed AS system with different model settings and problem parameters, we perform a comprehensive simulation study that incorporates several realistic operational features as well as an optimization model for patient to time-slot assignments. Computational results show that using this system can improve not only clinic utility but also patients’ AS experience significantly since it allows more patients to be appointed to one of their convenient dates. This simulation study presents a proof-of-concept for the proposed strategy while providing valuable managerial insights for implementing and operating such an AS system.Publication Metadata only A bi-criteria optimization model to analyze the impacts of electric vehicles on costs and emissions(Elsevier, 2017) N/A; N/A; Department of Industrial Engineering; Kabatepe, Bora; Türkay, Metin; Master Student; Faculty Member; Department of Industrial Engineering; Graduate School of Sciences and Engineering; College of Engineering; N/A; 24956Electric vehicles (EV) are emerging as a mobility solution to reduce emissions in the transportation sector. The studies environmental impact analysis of EVs in the literature are based on the average energy mix or pre-defined generation scenarios and construct policy recommendations with a cost minimization objective. However, the environmental performance of EVs depends on the source of the marginal electricity provided to the grid and single objective models do not provide a thorough analysis on the economic and environmental impacts of EVs. In this paper, these gaps are addressed by a four step methodology that analyzes the effects of EVs under different charging and market penetration scenarios. The methodology includes a bi-criteria optimization model representing the electricity market operations. The results from a real-life case analysis show that EVs decrease costs and emissions significantly compared to conventional vehicles.Publication Metadata only A multi-objective optimization approach for sustainable supply chains incorporating business strategy(IEEE, 2019) N/A; Department of Industrial Engineering; Bozgeyik, Esma Nur; Türkay, Metin; Master Student; Faculty Member; Department of Industrial Engineering; Graduate School of Sciences and Engineering; College of Engineering; N/A; 24956Sustainability is a necessity in the design and operation of supply chains. the triple bottom line (TBL) accounting of sustainability needs to incorporate economic, environmental and social pillars simultaneously in the decision making process. the business strategy can be developed to promote sustained growth, Also incorporating in the supply chain management issues as a business strategy rather than philanthropy. Deciding on the location of business facilities, supplier-manufacturer network, manufacturer-demand location network and the supplier- manufacturer relation strategy are among the important decisions in business strategy and supply chain management. However, there is a lack of theoretical work which analyzes the business strategy together with TBL concept of sustainability for the supply chain network design problem. in this paper, A methodological approach based on mathematical programming is proposed that conforms to the TBL accounting for supply chain network design problem from suppliers to customers embedded with business strategy and green energy usage option. a realistic case study is applied to the model. the results show that working with inclusive suppliers and using green energy are preferred with highest profit value.Publication Metadata only Stochastic models for the coordinated production and shipment problem in a supply chain(Pergamon-Elsevier Science Ltd, 2013) N/A; Department of Industrial Engineering; N/A; Department of Industrial Engineering; Kaya, Onur; Kubalı, Deniz; Örmeci, Lerzan; Faculty Member; Master Student; Faculty Member; Department of Industrial Engineering; College of Sciences; Graduate School of Sciences and Engineering; College of Engineering; 28405; N/A; 32863In this study, we consider the coordination of transportation and production policies between a single supplier and a single retailer in a stochastic environment. The supplier controls the production, holds inventory and ships the products to the retailer to satisfy the external demand. We model the system as a Markov decision process, and show that the optimal production and transportation decisions are complex and non-monotonic. Therefore, we analyze two widely-used shipment policies in the industry as well, namely time-based and quantity-based shipment policies in addition to a hybrid time-and-quantity based shipment policy. We numerically compare the performances of these policies with respect to the optimal policy and analyze the effects of the parameters in the system.Publication Metadata only Classification of 1,4-dihydropyridine calcium channel antagonists using the hyperbox approach(Amer Chemical Soc, 2007) N/A; N/A; Department of Industrial Engineering; Kahraman, Pınar; Türkay, Metin; Master Student; Faculty Member; Department of Industrial Engineering; Graduate School of Sciences and Engineering; College of Engineering; N/A; 24956The early prediction of activity-related characteristics of drug candidates is an important problem in drug design. Activity levels of drug candidates are classified as low or high depending on their IC50 values. Because the experimental determination of IC50 values for a vast number of molecules is both time-consuming and expensive, computational approaches are employed. In this work, we present a novel approach to classify the activities of drug molecules. We use the hyperbox classification method in combination with partial least-squares regression to determine the most relevant molecular descriptors of the drug molecules for an efficient classification. The effectiveness of the approach is illustrated on DHP derivatives. The results indicate that the proposed approach outperforms other approaches reported in the literature.Publication Metadata only Manufacturing parts sourcing with delayed transportation policy(Ieee, 2007) N/A; Department of Industrial Engineering; N/A; Department of Industrial Engineering; Department of Industrial Engineering; Erkan, Tuğçe; Sancak, Emre; Yıldırım, Emre Alper; Salman, Fatma Sibel; Undergraduate Student; Master Student; Faculty Member; Faculty Member; Department of Industrial Engineering; College of Engineering; N/A; College of Engineering; College of Engineering; N/A; N/A; 28415; 178838We propose a joint inventory and transportation policy for a manufacturer that needs to source multiple parts from a single supplier over a multiperiod planning horizon in order to facilitate its production plan. Instead of shipping trucks from the supplier to the manufacturer immediately whenever an order is given in a period, we allow delaying transportation to the next period in order to decrease the number of truck shipments with low truck loads. At the same time we maintain a minimum safety stock of each part at the manufacturer so that the production plan is not disrupted. We introduce a mixed integer programming model that represents the interdependency between ordering and transportation decisions and minimizes the sum of both transportation and inventory holding costs incurred to the manufacturer under the proposed policy. This model is utilized to improve the parts sourcing operations of a bus manufacturer in Istanbul with estimated sizeable savings on total costs.Publication Metadata only Constraint programming approach to quay crane scheduling problem(Pergamon-Elsevier Science Ltd, 2013) N/A; N/A; Department of Industrial Engineering; Ünsal, Özgür; Oğuz, Ceyda; PhD Student; Faculty Member; Department of Industrial Engineering; Graduate School of Sciences and Engineering; College of Engineering; College of Engineering; 328856; 6033This study presents a constraint programming (CP) model for the quay crane scheduling problem (QCSP), which occurs at container terminals, with realistic constraints such as safety margins, travel times and precedence relations. Next, QCSP with time windows and integrated crane assignment and scheduling problem, are discussed. The performance of the CP model is compared with that of algorithms presented in QCSP literature. The results of the computational experiments indicate that the CP model is able to produce good results while reducing the computational time, and is a robust and flexible alternative for different types of crane scheduling problems.Publication Metadata only Editorial: games and decisions in reliability and risk(Elsevier, 2018) Soyer, Refik; Department of Industrial Engineering; Özekici, Süleyman; Faculty Member; Department of Industrial Engineering; College of Engineering; 32631N/APublication Metadata only A coordinated production and shipment model in a supply chain(Elsevier Science Bv, 2013) N/A; Department of Industrial Engineering; N/A; Department of Industrial Engineering; Kaya, Onur; Kubalı, Deniz; Örmeci, Lerzan; Faculty Member; Master Student; Faculty Member; Department of Industrial Engineering; College of Sciences; Graduate School of Sciences and Engineering; College of Engineering; 28405; N/A; 32863In this study, we consider the coordination of transportation and production policies between a single supplier and a single retailer in a deterministic inventory system. In this supply chain, the customers are willing to wait at the expense of a waiting cost. Accordingly, the retailer does not hold inventory but accumulates the customer orders and satisfies them at a later time. The supplier produces the items, holds the inventory and ships the products to the retailer to satisfy the external demand. We investigate both a coordinated production/transportation model and a decentralized model. In the decentralized model, the retailer manages his own system and sends orders to the supplier, while the supplier determines her own production process and the amount to produce in an inventory replenishment cycle according to the order quantity of the retailer. However, in the coordinated model, the supplier makes all the decisions, so that she determines the length of the replenishment and transportation cycles as well as the shipment quantities to the retailer. We determine the structure of the optimal replenishment and transportation cycles hi both coordinated and decentralized models and the corresponding costs. Our computational results compare the optimal costs under the coordinated and decentralized models. We also numerically investigate the effects of several parameters on the optimal solutions.