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Permanent URI for this collectionhttps://hdl.handle.net/20.500.14288/6

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Department: search.filters.department.Department of Industrial EngineeringSponsors: search.filters.sponsors.TÜBİTAK

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    PublicationOpen Access
    Modelling and analysis of the impact of correlated inter-event data on production control using Markovian arrival processes
    (Springer, 2019) Department of Business Administration; Department of Industrial Engineering; N/A; Department of Business Administration; Department of Industrial Engineering; Tan, Barış; Dizbin, Nima Manafzadeh; Faculty Member; College of Administrative Sciences and Economics; College of Engineering; Graduate School of Business; 28600; N/A
    Empirical studies show that the inter-event times of a production system are correlated. However, most of the analytical studies for the analysis and control of production systems ignore correlation. In this study, we show that real-time data collected from a manufacturing system can be used to build a Markovian arrival processes (MAP) model that captures correlation in inter-event times. The obtained MAP model can then be used to control production in an effective way. We first present a comprehensive review on MAP modeling and MAP fitting methods applicable to manufacturing systems. Then we present results on the effectiveness of these fitting methods and discuss how the collected inter-event data can be used to represent the flow dynamics of a production system accurately. In order to study the impact of capturing the flow dynamics accurately on the performance of a production control system, we analyze a manufacturing system that is controlled by using a base-stock policy. We study the impact of correlation in inter-event times on the optimal base-stock level of the system numerically by employing the structural properties of the MAP. We show that ignoring correlated arrival or service process can lead to overestimation of the optimal base-stock level for negatively correlated processes, and underestimation for the positively correlated processes. We conclude that MAPs can be used to develop data-driven models and control manufacturing systems more effectively by using shop-floor inter-event data.
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    PublicationOpen Access
    Discovery of a small molecule that selectively destabilizes Cryptochrome 1 and enhances life span in p53 knockout mice
    (Nature Portfolio, 2022) Akyel, Yasemin Kübra; Korkmaz, Tuba; Selvi, Saba; Danış, İbrahim; İpek, Özgecan Savluğ; Aygenli, Fatih; Öztürk, Nuri; Öztürk, Narin; Ünal, Durişehvar Özer; Güzel, Mustafa; Okyar, Alper; N/A; Department of Chemical and Biological Engineering; Department of Industrial Engineering; Department of Chemical and Biological Engineering; Department of Industrial Engineering; Gül, Şeref; Gül, Zeynep Melis; Işın, Şafak; Özcan, Onur; Akarlar, Büşra; Taşkın, Ali Cihan; Türkay, Metin; Kavaklı, İbrahim Halil; Researcher; Other; Faculty Member; Faculty Member; Faculty Member; Koç University Research Center for Translational Medicine (KUTTAM) / Koç Üniversitesi Translasyonel Tıp Araştırma Merkezi (KUTTAM); College of Engineering; N/A; N/A; N/A; N/A; N/A; 291296; 105301; 24956; 40319
    Cryptochromes are negative transcriptional regulators of the circadian clock in mammals. It is not clear how reducing the level of endogenous CRY1 in mammals will affect circadian rhythm and the relation of such a decrease with apoptosis. Here, we discovered a molecule (M47) that destabilizes Cryptochrome 1 (CRY1) both in vitro and in vivo. The M47 selectively enhanced the degradation rate of CRY1 by increasing its ubiquitination and resulted in increasing the circadian period length of U2OS Bmal1-dLuc cells. In addition, subcellular fractionation studies from mice liver indicated that M47 increased degradation of the CRY1 in the nucleus. Furthermore, M47-mediated CRY1 reduction enhanced oxaliplatin-induced apoptosis in Ras-transformed p53 null fibroblast cells. Systemic repetitive administration of M47 increased the median lifespan of p53(-/-) mice by similar to 25%. Collectively our data suggest that M47 is a promising molecule to treat forms of cancer depending on the p53 mutation.
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    PublicationOpen Access
    A hierarchical solution approach for a multicommodity distribution problem under a special cost structure
    (Elsevier, 2012) Koca, Esra; Department of Industrial Engineering; Department of Industrial Engineering; Yıldırım, Emre Alper; Faculty Member; College of Engineering
    Motivated 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.
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    PublicationOpen 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; Department of Industrial Engineering; Örmeci, Lerzan; Faculty Member; College of Engineering; 32863
    We 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.
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    PublicationOpen Access
    Branch-and-price approaches for the network design problem with relays
    (Elsevier, 2018) Karasan, Oya Ekin; Yaman, Hande; Department of Industrial Engineering; Department of Industrial Engineering; Yıldız, Barış; Faculty Member; College of Engineering; 258791
    With different names and characteristics, relays play a crucial role in the design of transportation and telecommunication networks. In transportation networks, relays are strategic locations where exchange of drivers, trucks or mode of transportation takes place. In green transportation, relays become the refuelling/recharging stations extending the reach of alternative fuel vehicles. In telecommunication networks, relays are regenerators extending the reach of optical signals. We study the network design problem with relays and present a multi-commodity flow formulation and a branch-and-price algorithm to solve it. Motivated by the practical applications, we investigate the special case where each demand has a common designated source. In this special case, we can show that there exists an optimal design that is a tree. Using this fact, we replace the multi-commodity flow formulation with a tree formulation enhanced with Steiner cuts. Employing a branch-and-price-and-cut schema on this formulation, we are able to further extend computational efficiency to solve large problem instances.
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    PublicationOpen Access
    Rounding on the standard simplex: regular grids for global optimization
    (Springer, 2014) Bomze, Immanuel M.; Gollowitzer, Stefan; Department of Industrial Engineering; Department of Industrial Engineering; Yıldırım, Emre Alper; Faculty Member; College of Engineering
    Given 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.
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    PublicationOpen Access
    Exact and heuristic approaches based on noninterfering transmissions for joint gateway selection, time slot allocation, routing and power control for wireless mesh networks
    (Elsevier, 2017) Gökbayrak, Kağan; Department of Industrial Engineering; Department of Industrial Engineering; Yıldırım, Emre Alper; Faculty Member; College of Engineering
    Wireless mesh networks (WMNs) provide cost-effective alternatives for extending wireless communication over larger geographical areas. In this paper, given a WMN with its nodes and possible wireless links, we consider the problem of gateway node selection for connecting the network to the Internet along with operational problems such as routing, wireless transmission capacity allocation, and transmission power control for efficient use of wired and wireless resources. Under the assumption that each node of the WMN has a fixed traffic rate, our goal is to allocate capacities to the nodes in proportion to their traffic rates so as to maximize the minimum capacity-to-demand ratio, referred to as the service level. We adopt a time division multiple access (TDMA) scheme, in which a time frame on the same frequency channel is divided into several time slots and each node can transmit in one or more time slots. We propose two mixed integer linear programming formulations. The first formulation, which is based on individual transmissions in each time slot, is a straightforward extension of a previous formulation developed by the authors for a related problem under a different set of assumptions. The alternative formulation, on the other hand, is based on sets of noninterfering wireless transmissions. In contrast with the first formulation, the size of the alternative formulation is independent of the number of time slots in a frame. We identify simple necessary and sufficient conditions for simultaneous transmissions on different links of the network in the same time slot without any significant interference. Our characterization, as a byproduct, prescribes a power level for each of the transmitting nodes. Motivated by this characterization, we propose a simple scheme to enumerate all sets of noninterfering transmissions, which is used as an input for the alternative formulation. We also introduce a set of valid inequalities for both formulations. For large instances, we propose a three-stage heuristic approach. In the first stage, we solve a partial relaxation of our alternative optimization model and determine the gateway locations. This stage also provides an upper bound on the optimal service level. In the second stage, a routing tree is constructed for each gateway node computed in the first stage. Finally, in the third stage, the alternative optimization model is solved by fixing the resulting gateway locations and the routing trees from the previous two stages. For even larger networks, we propose a heuristic approach for solving the partial relaxation in the first stage using a neighborhood search on gateway locations. Our computational results demonstrate the promising performance of our exact and heuristic approaches and the valid inequalities
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    PublicationOpen Access
    Regenerator location problem in flexible optical networks
    (Informs, 2017) Karasan, Oya Ekin; Department of Industrial Engineering; Department of Industrial Engineering; Yıldız, Barış; Faculty Member; College of Engineering; 258791
    In this study, we introduce the regenerator location problem in flexible optical networks. With a given traffic demand, the regenerator location problem in flexible optical networks considers the regenerator location, routing, bandwidth allocation, and modulation selection problems jointly to satisfy data transfer demands with the minimum cost regenerator deployment. We propose a novel branch-and-price algorithm for this challenging problem. Using real-world network topologies, we conduct extensive numerical experiments to both test the performance of the proposed solution methodology and evaluate the practical benefits of flexible optical networks. In particular, our results show that, making routing, bandwidth allocation, modulation selection, and regenerator placement decisions in a joint manner, it is possible to obtain drastic capacity enhancements when only a very modest portion of the nodes is endowed with the signal regeneration capability.
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    PublicationOpen Access
    Joint gateway selection, transmission slot assignment, routing and power control for wireless mesh networks
    (Elsevier, 2013) Gökbayrak, Kağan; Department of Industrial Engineering; Department of Industrial Engineering; Yıldırım, Emre Alper; Faculty Member; College of Engineering
    Wireless 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.
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    PublicationOpen Access
    An integrated data-driven method using deep learning for a newsvendor problem with unobservable features
    (Elsevier, 2022) Pirayesh Neghab, D.; Khayyati, S.; Department of Industrial Engineering; Department of Industrial Engineering; Karaesmen, Fikri; Faculty Member; College of Engineering; 3579
    We consider a single-period inventory problem with random demand with both directly observable and unobservable features that impact the demand distribution. With the recent advances in data collection and analysis technologies, data-driven approaches to classical inventory management problems have gained traction. Specially, machine learning methods are increasingly being integrated into optimization problems. Although data-driven approaches have been developed for the newsvendor problem, they often consider learning from the available data and optimizing the system separate tasks to be performed in sequence. One of the setbacks of this approach is that in the learning phase, costly and cheap mistakes receive equal attention and, in the optimization phase, the optimizer is blind to the confidence of the learner in its estimates for different regions of the problem. To remedy this, we consider an integrated learning and optimization problem for optimizing a newsvendor's strategy facing a complex correlated demand with additional information about the unobservable state of the system. We give an algorithm based on integrating optimization, neural networks and hidden Markov models and use numerical experiments to show the efficiency of our method. In an empirical experiment, the method outperforms the best competitor benchmark by more than 27%, on average, in terms of the system cost. We give further analyses of the performance of the method using a set of numerical experiments.