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Permanent URI for this collectionhttps://hdl.handle.net/20.500.14288/3
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Publication Metadata only The analysis of fatal aviation accidents more than 100 dead passengers: an application of machine learning(Springer India, 2022) Inan, Tuzun Tolga; Department of Computer Engineering; İnan, Neslihan Gökmen; Teaching Faculty; Department of Computer Engineering; College of Engineering; 285581Safety is the most prominent factor that affected accidents in civil aviation history. In safety concept, the primary factors are defined as human, technical, and sabotage/terrorism factors. Despite these primary causes, there have other factors that have an impact to accidents. The study aims to determine the affected factors of the 220 accidents that were ended with more than 100 dead passengers by the primary causes and the other factors such as aircraft type, total distance, the phase of flight, number of total passengers, and time period of the accident. All these factors aims to classify the rate of survivor/non-survivor passenger rate according to most fatal accidents. It is used logistic regression and discriminant analysis for multivariate statistical analyses comparing the machine learning approaches to show the algorithms' robustness. At the end of the analysis, it is seen that machine learning techniques have better performance than multivariate statistical methods in related to accuracy, false-positive rate, and false-negative rates. The managerial aim of this study is related to find the most important factors that affected the most fatal accidents. These factors are found as; the phase of flight, the primary cause, and total passenger numbers according to machine learning and multivariate statistical models for classifying the rate of survivor/non-survivor passenger numbers.Publication Metadata only Characterizing the performance of process flexibility structures(Elsevier, 2007) N/A; Department of Business Administration; Department of Industrial Engineering; Karaesmen, Zeynep Akşin; Karaesmen, Fikri; Faculty Member; Faculty Member; Department of Business Administration; Department of Industrial Engineering; College of Administrative Sciences and Economics; College of Engineering; 4534; 3579The objective is to identify preferred flexibility structures in service or manufacturing systems, when demand is random and capacity is finite. Considering a network flow type model as the basis of the analysis, general structural properties of flexibility design pertaining to the marginal values of flexibility and capacity are identified.Publication Metadata only A tandem queueing model with coupled processors(Elsevier, 2003) Resing, Jacques; Department of Industrial Engineering; Örmeci, Lerzan; Faculty Member; Department of Industrial Engineering; College of Engineering; 32863We consider a tandem queue with coupled processors and analyze the two-dimensional Markov process representing the numbers of jobs in the two stations. A functional equation for the generating function of the stationary distribution of this two-dimensional process is derived and solved through the theory of Riemann-Hilbert boundary value problems.Publication Metadata only Dynamic pricing and scheduling in a multi-class single-server queueing system(Springer, 2011) Cil, Eren Basar; Department of Industrial Engineering; Department of Industrial Engineering; Karaesmen, Fikri; Örmeci, Lerzan; Faculty Member; Faculty Member; Department of Industrial Engineering; College of Engineering; College of Engineering; 3579; 32863This paper investigates an optimal sequencing and dynamic pricing problem for a two-class queueing system. Using a Markov Decision Process based model, we obtain structural characterizations of optimal policies. In particular, it is shown that the optimal pricing policy depends on the entire queue length vector but some monotonicity results prevail as the composition of this vector changes. A numerical study finds that static pricing policies may have significant suboptimality but simple dynamic pricing policies perform well in most situations.Publication Metadata only Effects of system parameters on the optimal policy structure in a class of queueing control problems(Springer, 2009) Cil, Eren Basar; Department of Industrial Engineering; Department of Industrial Engineering; Örmeci, Lerzan; Karaesmen, Fikri; Faculty Member; Faculty Member; Department of Industrial Engineering; College of Engineering; College of Engineering; 32863; 3579This paper studies a class of queueing control problems involving commonly used control mechanisms such as admission control and pricing. It is well established that in a number of these problems, there is an optimal policy that can be described by a few parameters. From a design point of view, it is useful to understand how such an optimal policy varies with changes in system parameters. We present a general framework to investigate the policy implications of the changes in system parameters by using event-based dynamic programming. In this framework, the control model is represented by a number of common operators, and the effect of system parameters on the structured optimal policy is analyzed for each individual operator. Whenever a queueing control problem can be modeled by these operators, the effects of system parameters on the optimal policy follow from this analysis.Publication Metadata only Parallel machine scheduling with additional resources: a lagrangian-based constraint programming approach(Springer, 2011) Edis, Emrah B.; Department of Industrial Engineering; Oğuz, Ceyda; Faculty Member; Department of Industrial Engineering; College of Engineering; 6033This study deals with an unrelated parallel machine scheduling problem with one additional resource type (e. g., machine operators). The objective is to minimize the total completion time. After giving the integer programming model of the problem, a Lagrangian relaxation problem (LRP) is introduced by relaxing the constraint set concerning the additional resource. A general subgradient optimization procedure is applied to a series of LRPs to maximize the lower bound for the original problem. To generate efficient upper bounds for the original problem, a constraint programming (CP) model is applied by taking the LRP solutions as input regarding the machine assignments. For the problem, a pure CP model is also developed to evaluate its performance. All the solution approaches are evaluated through a range of test problems. The initial computational results show that Lagrangian-based CP approach produces promising results especially for larger problem sizes.Publication Metadata only Two-machine flow shop scheduling with common due window to minimize weighted number of early and tardy jobs(Wiley, 2009) Yeung, Wing-Kwan; Cheng, Tai Chiu Edwin; Department of Industrial Engineering; Oğuz, Ceyda; Faculty Member; Department of Industrial Engineering; College of Engineering; 6033This article studies two due window scheduling problems to minimize the weighted number of early and tardy jobs in a two-machine flow shop, where the window size is externally determined. These new scheduling models have many practical applications in real life. However, results on these problems have rarely appeared in the literature because of a lack of structural and optimality properties for solving them. In this article, we derive several dominance properties and theorems, including elimination rules and sequencing rules based on Johnson's order, lower bounds on the penalty, and upper bounds on the window location, which help to significantly trim the search space for the problems. We further show that the problems are NP-hard in the ordinary sense only. We finally develop efficient pseudopolynomial dynamic programming algorithms for solving the problems.Publication Metadata only Constant risk aversion in stochastic contests with exponential completion times(Wiley, 2019) Rothblum, Uriel G.; Department of Industrial Engineering; Canbolat, Pelin Gülşah; Faculty Member; Department of Industrial Engineering; College of Engineering; 108242This article analyzes a class of stochastic contests among multiple players under risk-averse exponential utility. In these contests, players compete over the completion of a task by simultaneously deciding on their investment, which determines how fast they complete the task. The completion time of the task for each player is assumed to be an exponentially distributed random variable with rate linear in the player's investment and the completion times of different players are assumed to be stochastically independent. The player that completes the task first earns a prize whereas the remaining players earn nothing. The article establishes a one-to-one correspondence between the Nash equilibrium of this contest with respect to risk-averse exponential utilities and the nonnegative solution of a nonlinear equation. Using the properties of the latter, it proves the existence and the uniqueness of the Nash equilibrium, and provides an efficient method to compute it. It exploits the resulting representation of the equilibrium investments to determine the effects of risk aversion and the differences between the outcome of the Nash equilibrium and that of a centralized version.(c) 2016 Wiley Periodicals, Inc. Naval Research Logistics 66:4-14, 2019