Department of Industrial Engineering

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  • ItemOpen Access
    Can accessing much data reshape the theory? Inventory theory under the challenge of data-driven systems
    (Elsevier, 2022-08-24) Erkip, Nesim Kohen; Erkip, Nesim Kohen
    In this review, we discuss the data-driven systems and their effects on the implementation of the inventory theory. After overviewing the theory briefly, we group the data-driven approaches to simplify exposition. We consider the use of available data to estimate the parameters of more complex models, and propose developing the theory in that direction, as well. As a pedagogical example, an extension of the standard EOQ model with heterogenous customers is presented. The review proposes a research agenda for inventory problems and concludes with discussing challenges for the future.
  • ItemOpen Access
    A unifying network modeling approach for codon optimization
    (Oxford University Press, 2022-06-28) Karaşan, Oya; Şen, Alper; Tiryaki, Banu; Çiçek, A. Ercüment; Karaşan, Oya; Şen, Alper; Tiryaki, Banu; Çiçek, A. Ercüment
    Motivation: Synthesizing genes to be expressed in other organisms is an essential tool in biotechnology. While the many-to-one mapping from codons to amino acids makes the genetic code degenerate, codon usage in a particular organism is not random either. This bias in codon use may have a remarkable effect on the level of gene expression. A number of measures have been developed to quantify a given codon sequence’s strength to express a gene in a host organism. Codon optimization aims to find a codon sequence that will optimize one or more of these measures. Efficient computational approaches are needed since the possible number of codon sequences grows exponentially as the number of amino acids increases. Results: We develop a unifying modeling approach for codon optimization. With our mathematical formulations based on graph/network representations of amino acid sequences, any combination of measures can be optimized in the same framework by finding a path satisfying additional limitations in an acyclic layered network. We tested our approach on bi-objectives commonly used in the literature, namely, Codon Pair Bias versus Codon Adaptation Index and Relative Codon Pair Bias versus Relative Codon Bias. However, our framework is general enough to handle any number of objectives concurrently with certain restrictions or preferences on the use of specific nucleotide sequences. We implemented our models using Python’s Gurobi interface and showed the efficacy of our approach even for the largest proteins available. We also provided experimentation showing that highly expressed genes have objective values close to the optimized values in the bi-objective codon design problem.
  • ItemOpen Access
    Logistics planning of cash transfer to Syrian refugees in Turkey
    (Elsevier B.V., 2021-05-06) Kian, Ramez; Erdoğan, Güneş; de Leeuw, Sander; Salman F., Sibel; Sabet, Ehsan; Kara, Bahar Y.; Demir, Muhittin H.; Kara, Bahar Y.
    This paper addresses a humanitarian logistics problem connected with the Syrian refugee crisis. The ongoing conflict in Syria has caused displacement of millions of people. Cash-based interventions play an important role in aiding people in the post-crisis period to enhance their well-being in the medium and longer term. The paper presents a study on how to design a network of administrative facilities to support the roll-out of cash-based interventions. The resulting multi-level network consists of a central registration facility, local temporary facilities, mobile facilities and vehicles for door-to-door visits. The goal is to reach the maximum number of eligible beneficiaries within a specified time period while minimizing logistics costs, subject to a limit on total security risk exposure. A mixed integer programming model is formulated to optimize the inter-related facility location and routing decisions under multiple objectives. The authors develop a hierarchical multi-objective metaheuristic algorithm to obtain efficient solutions. An application of the model and the solution algorithm to real data from a region in the southeast of Turkey is presented, with associated managerial insights. © 2021 The Author(s)
  • ItemOpen Access
    Detection and identification of changes of hidden Markov chains: Asymptotic theory
    (Springer Science and Business Media B.V., 2021-10-06) Dayanık, Savaş; Yamazaki, Kazutoshi; Dayanık, Savaş
    This paper revisits a unified framework of sequential change-point detection and hypothesis testing modeled using hidden Markov chains and develops its asymptotic theory. Given a sequence of observations whose distributions are dependent on a hidden Markov chain, the objective is to quickly detect critical events, modeled by the first time the Markov chain leaves a specific set of states, and to accurately identify the class of states that the Markov chain enters. We propose computationally tractable sequential detection and identification strategies and obtain sufficient conditions for the asymptotic optimality in two Bayesian formulations. Numerical examples are provided to confirm the asymptotic optimality. © 2021, The Author(s).
  • ItemOpen Access
    Logistics of temporary testing centers for coronavirus disease
    (Elsevier, 2022-11-04) Ozdemir, Irmak; Dora, Manoj; Dursunoğlu, Çağla Fatma; Yetiş Kara, Bahar; Ozdemir, Irmak; Dursunoğlu, Çağla Fatma; Yetiş Kara, Bahar
    The ongoing COVID-19 pandemic has caused the death of millions of people, and PCR testing is widely used as the gold standard method to detect the infections to restrict the outbreak. Through the interviews conducted with people from the field in South Korea, the UK, and Turkey, we have found that there are numerous testing strategies worldwide. Those testing strategies include drive-through and home delivery testing capabilities, local test sites, and mobile test centers. Our primary motivation is to propose a generic model based on the best practices in the UK and South Korea. Also, we aim to present a case study on Turkey for the implementation of vital procedures and increase their availability. This paper represents a study on how to construct a temporary testing logistics system during the initial phases of pandemics to increase the availability of PCR testing with the primary objective of maximizing total sample collection. The design also considers minimizing the maximum walking distance to increase the convenience of sample collection for the people living in the neighborhoods. The proposed system consists of temporary testing centers and a central laboratory. Temporary testing centers perform direct tours to the potential areas to collect samples and bring the collected sample to the designated central laboratories located at central hospitals. Moreover, to represent the non-linear inheritance of the pandemic progress within a population, we consider diminishing sample potentials over time and coverage. This new problem is defined as an extension of the Selective Vehicle Routing Problem and Covering Tour Problem. We propose a mathematical model and four two-stage math-heuristic algorithms to determine the location and routing of the temporary testing centers and their lengths of stay at each visited location. The performances of the proposed solution methodologies are tested on two data sets. The first set is constructed by the confirmed cases of the districts of Seoul, Korea, and by the interview of health personnel of H+ Yangji Hospital COVID-19 semi-mobile booth application, and the second set is constructed by 99 hospital/health centers from distinct neighborhoods of 22 districts of Istanbul, Turkey. The Pareto set of optimum solutions is generated based on total sample collection and maximum walking distance. Finally, sensitivity analyses on some design parameters are conducted. © 2022 Elsevier Ltd
  • ItemOpen Access
    Mobile healthcare services in rural areas: An application with periodic location routing problem
    (Springer Science and Business Media Deutschland GmbH, 2022-03-15) Savaşer, Sinem Kınay; Kara, Bahar Yetiş; Kara, Bahar Yetiş
    In this study, we focus on the delivery of mobile healthcare services in rural areas, where doctors visit remote villages which do not have a healthcare facility nearby. The aim is to increase the accessibility of healthcare services for such population centers. We aim to determine the village assignments of the doctors, their monthly visit schedules and base hospitals where they start and end their tours. We model this as a periodic location routing problem and use the policies of Ministry of Health of Turkey as a basis for our mathematical formulation. These policies include the essential components of mobile healthcare services, namely, continuity of care and determining evenly distributed periodic visits. We determine the visit schedules, i.e. routes, of doctors endogenously while satisfying these policies. We also develop a heuristic algorithm based on a cluster first-route second approach and solve larger instances more effectively. The computational experiments support that this solution methodology can effectively find optimal or near-optimal solutions and improve the computational times significantly.
  • ItemOpen Access
    Investigating flank face friction during precision micro cutting of commercially pure titanium via plunging tests with diamond grooving tools
    (Elsevier, 2022-01) Karpat, Yiğit; Karpat, Yiğit
    This study investigates flank face friction while micro machining commercially pure titanium (cp-Ti grade 2) work material considering size effects. It is important to understand friction phenomena at the tool flank and work material surface since they affect the surface integrity of the machined parts. A single crystal diamond grooving tool is used in machining experiments to reduce the influence of cutting edge radius. In addition, plunging type of cutting experiments were performed to investigate the influence of flank face contact on the machined surface. A friction model which is based on work and tool material properties is proposed to model the contribution of adhesion and deformation of the flank face coefficient of friction. The results show that for the cp-Ti and diamond tool pair, adhesion seems to be the dominant model of friction and also contributes to the size effect. The deformation friction becomes more dominant during the chip formation stage. When cutting edge effect is eliminated, the influences of flank and rake face friction on the size effect are shown.
  • ItemOpen Access
    Operational benefit of transforming cascade hydropower stations into pumped hydro energy storage systems
    (Elsevier, 2022-07) Toufani, Parinaz; Nadar, Emre; Kocaman, Ayse Selin; Toufani, Parinaz; Nadar, Emre; Kocaman, Ayse Selin
    This study evaluates the potential benefit of retrofitting existing conventional cascade hydropower stations (CCHSs) with reversible turbines so as to operate them as pumped hydro energy storage (PHES) systems. We examine the energy generation and storage problem for a CCHS with two connected reservoirs that can be transformed into a PHES system in a market setting where the electricity price can be negative. We formulate this problem as a stochastic dynamic program (SDP) under uncertainty in the streamflow rate and electricity price. We analytically derive an upper bound on the profit improvement that can be obtained from the PHES transformation. We conduct numerical experiments with data-calibrated time series models and observe that the PHES system provides a greater benefit under more limited streamflow conditions or more frequently observed negative prices.
  • ItemOpen Access
    A model-based investigation of tool-chip friction during precision micro cutting of commercially pure titanium alloy
    (Inderscience Publishers, 2022) Aksin, Alp; Karpat, Yiğit; Aksin, Alp; Karpat, Yiğit
    Understanding interaction between the cutting tool edge radius and the work material is essential to identify the conditions leading to superior surface finish during the micromachining process. The interaction between friction angle and effective rake angle has been investigated based on a slip-line field-based machining model from the literature. Machining forces and cut chip thickness values were obtained from orthogonal cutting tests and employed in the process model. The proposed model also allows for calculating material properties such as shear flow stress and fracture toughness. The proposed model can successfully simulate machining forces during shearing-dominated machining conditions. The results showed the importance of flank and rake face friction in micro-scale machining.
  • ItemOpen Access
    End-of-life inventory management problem: results and insights
    (Elsevier, 2021-09-30) Ozyoruk, E.; Erkip, Nesim Kohen; Ararat, Çağın; Erkip, Nesim Kohen
    We consider a manufacturer who manages the end-of-life phase and takes one of the three actions at each period: (1) place an order, (2) use existing inventory, (3) stop holding inventory and use an outside/alternative source. Two examples of this source are discounts for a new generation product and delegating operations. Demand is described by a non-homogeneous Poisson process, and the decision to stop holding inventory is described by a stopping time. After formulating this problem as an optimal stopping problem with additional decisions and presenting its dynamic programming algorithm, we use martingale theory to facilitate the calculation of the value function. Moreover, we show analytical results to understand the additional difficulties of the problem solved, as well as structural results on optimal stopping times. Furthermore, we devise an expandable taxonomy and categorize the models in the literature. Analytical insights from the models as well as an extensive numerical analysis show the value of our approach. The results indicate that the loss can be high in case the manufacturer does not exploit flexibility in placing orders or use an outside source. Several managerial insights are obtained through numerical analysis as well as structural results to facilitate decision-making during the end-of-life horizon. © 2021 Elsevier B.V.
  • ItemOpen Access
    Solution approaches for equitable multiobjective integer programming problems
    (Springer, 2022-04) Bashir, Bashir; Karsu, Özlem; Bashir, Bashir; Karsu, Özlem
    We consider multi-objective optimization problems where the decision maker (DM) has equity concerns. We assume that the preference model of the DM satisfies properties related to inequity-aversion, hence we focus on finding nondominated solutions in line with the properties of inequity-averse preferences, namely the equitably nondominated solutions. We discuss two algorithms for finding good subsets of equitably nondominated solutions. The first approach is an extension of an interactive approach developed for finding the most preferred nondominated solution when the utility function is assumed to be quasiconcave. We find the most preferred equitably nondominated solution when the utility function is assumed to be symmetric quasiconcave. In the second approach we generate an evenly distributed subset of the set of equitably nondominated solutions to be considered further by the DM. We show the computational feasibility of the two algorithms on equitable multi-objective knapsack problem, in which projects in different categories are to be funded subject to a limited budget. We perform experiments to show and discuss the performances of the algorithms. © 2020, Springer Science+Business Media, LLC, part of Springer Nature.
  • ItemOpen Access
    Robust stock assortment and cutting under defects in automotive glass production
    (Wiley-Blackwell Publishing, Inc., 2022-07-23) Arbib, Claudio; Marinelli, Fabrizio; Pınar, Mustafa Ç.; Pizzuti, Andrea; Pınar, Mustafa Ç.
    We address an assortment-and-cutting problem arising in the glass industry. The objective is to provide minimum waste solutions that are robust against such raw material imperfections as those possibly occurring with float glass production technology. The stochastic realization of defects is modeled as a spatial Poisson point process. A mixed integer program in the classical vein of robust optimization is presented and tested on data taken from a real plant application. Defective final products must in any case be discarded as waste but, if a recourse strategy is adopted, faults in glass sheets can sometimes be recovered. Closed forms for the computation of faulty item probabilities are provided in simple cases, and obtained via Monte Carlo simulation in more complex ones. The computational results demonstrate the benefits of the robust approach in terms of the reduction of back-orders and overproduction, thereby showing that recourse strategies can enable nonnegligible improvements. Encouraged by this result, the management is presently evaluating the possibility of adopting the proposed model in plant operation.
  • ItemOpen Access
    Human exposure to aerosol from indoor gas stove cooking and the resulting nervous system responses
    (Wiley, 2022-01-17) Torkmahalleh, Mehdi Amouei; Naseri, Motahareh; Nurzhan, Sholpan; Gabdrashova, Raikhangul; Bekezhankyzy, Zhibek; Gimnkhan, Aidana; Malekipirbazari, Milad; Jouzizadeh, Mojtaba; Tabesh, Mahsa; Farrokhi, Hamta; Mehri-Dehnavi, Hossein; Khanbabaie, Reza; Sadeghi, Sahar; Khatir, Ali Alizadeh; Sabanov, Sergei; Buonanno, Giorgio; Hopke, Philip K.; Cassee, Flemming; Crape, Byron; Malekipirbazari, Milad
    Our knowledge of the effects of exposure to indoor ultrafine particles (sub-100 nm, #/cm3) on human brain activity is very limited. The effects of cooking ultrafine particles (UFP) on healthy adults were assessed using an electroencephalograph (EEGs) for brain response. Peak ultrafine particle concentrations were approximately 3 × 105 particle/cm3, and the average level was 1.64 × 105 particle/cm3. The average particle number emission rate (S) and the average number decay rate (a+k) for chicken frying in brain experiments were calculated to be 2.82 × 1012 (SD = 1.83 × 1012, R2 = 0.91, p = 0.0013) particles/min, 0.47 (SD = 0.30, R2 = 0.90, p < 0.0001) min−1, respectively. EEGs were recorded before and during cooking (14 min) and 30 min after the cooking sessions. The brain fast-wave band (beta) decreased during exposure, similar to people with neurodegenerative diseases. It subsequently increased to its pre-exposure condition for 70% of the study participants after 30 min. The brain slow-wave band to fast-wave band ratio (theta/beta ratio) increased during and after exposure, similar to observed behavior in early-stage Alzheimer's disease (AD) patients. The brain then tended to return to its normal condition within 30 min following the exposure. This study suggests that chronically exposed people to high concentrations of cooking aerosol might progress toward AD.
  • ItemOpen Access
    Fair resource allocation: Using welfare-based dominance constraints
    (Elsevier, 2022-03-01) Argyris, N.; Karsu, Özlem; Yavuz, Mirel; Karsu, Özlem
    In this paper we consider the problem of supporting resource allocation decisions affecting multiple beneficiaries. Such problems inherently involve efficiency-fairness trade-offs. We introduce a new approach based on the paradigm of maximizing efficiency subject to constraints to ensure that the decision is acceptably fair. In contrast to existing literature, we incorporate fairness in the form of welfare dominance, ensuring that the resultant distribution of benefits to beneficiaries is at least as good as some reference distribution with respect to a set of social welfare functions that satisfy commonly accepted efficiency and fairness related axioms. We introduce a practical means to parameterize the problem, which allows for excluding welfare functions that are deemed insufficiently or overly sensitive to inequality. This allows for analyzing the impact of changes in inequality aversion on efficiency, thus revealing the trade-off between efficiency and fairness. We develop tractable reformulations for the resulting non-linear multi-level optimization problems. We then extend this approach for cases where resources are allocated to groups of individuals with different sizes. We demonstrate the potential use of the suggested framework on two case studies: a workload allocation problem and a healthcare provisioning problem.
  • ItemOpen Access
    Optimal dynamic multi-keyword bidding policy of an advertiser in search-based advertising
    (Springer, 2022-02) Dayanık, Savaş; Dayanık, Savaş
    Sponsored search advertisement allows advertisers to target their messages to appropriate customer segments at low costs. While search engines are interested in auction mechanisms that boost their revenues, advertisers seek optimal bidding strategies to increase their net sale revenues for multiple keywords under strict daily budget constraints in an environment where keyword query arrivals, competitor bid amounts, and user purchases are random. We focus on the advertiser’s question and formulate her optimal intraday dynamic multi-keyword bidding problem as a continuous-time stochastic optimization problem. We solve the problem, characterize an optimal policy, and bring a numerical algorithm for implementation. We also illustrate our optimal bidding policy and its benefits over heuristic solutions on numerical examples.
  • ItemOpen Access
    Surface integrity of monocrystalline silicon nanostructured with engineered multi-tip diamond tools
    (Springer, 2022-05) Karpat, Yiğit; Karpat, Yiğit
    The ability to fabricate micro/nanostructures on large surface areas would enhance product performance in optics and solar energy systems, where maintaining high productivity is also critical. Recently, diamond tools structured with nanoscale features have been used to machine ductile materials such as copper and electroless nickel. This study uses engineered diamond tools featuring multi-tip cutting edges to investigate nanoscale grooving of silicon. Multi-tip cutting edges create a certain level of pressure and temperature at the cutting zone, which leads to phase transformations in silicon. Experiments were performed using an ultra-precision machining setup to identify conditions leading to nanoscale ductile-mode machining of silicon. As nanogrooves reach 300 nm depth, hexagonal-Si (Si-IV) phase formation was observed based on laser Raman spectroscopy measurements. Hexagonal allotropes of silicon are known to improve light absorption of silicon. Additional experiments with non-structured diamond tools did not yield any Si-IV phase transformation, indicating the importance of obtaining necessary pressure and temperature conditions at the cutting zone.
  • ItemEmbargo
    A conditional β -mean approach to risk-averse stochastic multiple allocation hub location problems
    (Elsevier Ltd, 2022-01-29) Ghaffarinasab, N.; Yetiş Kara, Bahar; Yetiş Kara, Bahar
    This paper addresses risk-averse stochastic hub location problems where the risk is measured using the conditional β -mean criterion. Three variants of the classical multiple allocation hub location problem, namely the p-hub median, the p-hub maximal covering, and the weighted p-hub center problems are studied under demand data uncertainty represented by a finite set of scenarios. Novel mixed-integer linear programming formulations are proposed for the problems and exact algorithms based on Benders decomposition are developed for solving large instances of the problems. A large set of computational tests are conducted so that the efficiency of the proposed algorithms is proved and the effect of various input parameters on the optimal solutions is analyzed.
  • ItemEmbargo
    Resilient airline scheduling to minimize delay risks
    (Elsevier Ltd, 2022-06-06) Şi̇mşek, D.; Aktürk, M. Seli̇m; Aktürk, M. Seli̇m
    Airlines tend to design their flights schedules with the primary concern of the minimization of operational costs. However, the recently emerging idea of resilient scheduling defined as staying operational in case of unexpected disruptions and adaptability should be of great importance for airlines as well due to the high opportunity costs caused by the flight cancellations and passenger inconvenience caused by delays in the schedule. In this study, we integrate resilient airline schedule design, aircraft routing and fleet assignment problems with uncertain non-cruise times and controllable cruise times. We follow a data-driven method to estimate flight delay probabilities to calculate the airport congestion coefficients required for the probability distributions of non-cruise time random variables. We formulate the problem as a bi-criteria nonlinear mixed integer mathematical model with chance constraints. The nonlinearity caused by the fuel consumption and CO2 emission function associated with the controllable cruise times in our first objective is handled by second order conic inequalities. We minimize the total absolute deviation of the aircraft path variability’s from the average in our second objective to generate balanced schedules in terms of resilience. We compare the recovery performances of our proposed schedules to the minimum cost schedules by a scenario-based posterior analysis.
  • ItemEmbargo
    A two-stage decision dependent stochastic approach for airline flight network expansion
    (Elsevier Ltd, 2022-02-28) Şafak, Ö.; Çavuş, Özlem; Aktürk, M. Selim; Çavuş, Özlem; Aktürk, M. Selim
    Airlines need to expand their flight networks with developing new routes and introducing more flights to increase their market share. In this work, we propose a two-stage stochastic mixed integer nonlinear program (MINLP), which expands an existing flight schedule by operating new flights either with existing fleet resources or a leased aircraft while considering the impact of departure time decisions on the probability distribution of random demand. Moreover, our study helps an airline to link a strategic decision of leasing an aircraft to the tactical aircraft assignment decisions by considering fuel efficiency and seat capacity of the aircraft alternatives in response to new passenger demand. However, the large number of scenarios, nonlinear fuel burn function and nonlinearities due to the decision dependent probabilities become main challenges of solving the problem. In order to deal with the computational requirements of a two-stage stochastic MINLP with decision dependent probabilities, we propose strong conic quadratic and McCormick inequalities, and an exact scenario group wise decomposition algorithm along with a new bounding method. In our computational results, we clearly demonstrate the effectiveness of proposed decomposition algorithm and the strength of the reformulations.
  • ItemEmbargo
    The stratified p-hub center and p-hub maximal covering problems
    (Elsevier Ltd, 2022-02-01) Yetiş Kara, Bahar; Ghaffarinasab, N.; Campbell, J. F.; Yetiş Kara, Bahar
    Hub networks are the foundation of many transportation and distribution systems, and real-world hub networks often transport freight or passengers of different service classes. This paper introduces the stratified multiple allocation p-hub center and p-hub maximal covering problems where the traffic corresponding to each origin–destination (O/D) pair is divided into different strata each having a specific service level requirement. The problems are formulated as mixed-integer linear programming (MILP) models and efficient Benders decomposition algorithms are developed for solving large instances. Extensive computational experiments are conducted to demonstrate the efficiency of the proposed mathematical models and the solution algorithms. MILP formulations are also proposed for the generalized versions of the problems that include fixed set-up costs for hubs and hub arcs. Results indicate that the optimal sets of hub locations and hub arcs when considering different strata can be quite dissimilar to those of the traditional p-hub center or p-hub maximal covering problem, but are similar to those of hierarchical hub location problems. Furthermore, models are provided and solved for multi-modal stratified hub location problems with fixed setup costs for hubs and hub arcs. Optimal results show a wide range of network topologies that can be generated, as compared to the classical versions.