Researcher:
Özekici, Süleyman

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Süleyman

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Özekici

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Özekici, Süleyman

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Researcher Of Publications: search.filters.isAuthorOfPublication.59f45f0c-3694-400a-88f6-aee1412686a0

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Now showing 1 - 10 of 40
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    Parallel computing in Asian option pricing
    (Elsevier Science Bv, 2007) Sak, Halis; Boduroglu, Ilkay; Department of Industrial Engineering; Özekici, Süleyman; Faculty Member; Department of Industrial Engineering; College of Engineering; 32631
    We discuss the use of parallel computing in Asian option pricing and evaluate the efficiency of various algorithms. We only focus on "backward-starting fixed strike" Asian options that are continuously averaged. We implement a partial differential equation (PDE) approach that involves a single state variable to price the Asian option, and implement the same methodology to price a standard European option to check for accuracy. A parabolic PDE is solved by using both explicit and Crank-Nicolson's implicit finite-difference methods. In particular, we look for algorithms designed for implementing the computations in massively parallel processors (MPP). We evaluate the performance of the algorithms by comparing the numerical results with respect to accuracy and wall-clock time of code executions. Codes are executed on a Linux PC cluster.
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    Portfolio optimization in stochastic markets
    (Springer Heidelberg, 2006) Cakmak, U; Department of Industrial Engineering; Özekici, Süleyman; Faculty Member; Department of Industrial Engineering; College of Engineering; 32631
    We consider a multiperiod mean-variance model where the model parameters change according to a stochastic market. The mean vector and covariance matrix of the random returns of risky assets all depend on the state of the market during any period where the market process is assumed to follow a Markov chain. Dynamic programming is used to solve an auxiliary problem which, in turn, gives the efficient frontier of the mean-variance formulation. An explicit expression is obtained for the efficient frontier and an illustrative example is given to demonstrate the application of the procedure.
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    MTTF and availability of semi-Markov missions with non-identical generally distributed component lifetimes
    (Taylor & Francis) Cekyay, Bora; Department of Industrial Engineering; Özekici, Süleyman; Faculty Member; Department of Industrial Engineering; College of Engineering; 32631
    We analyze mean time to failure and availability of systems that perform semi-Markov missions. The mission process is the minimal semi-Markov process associated with a Markov renewal process. Therefore, the successive phases of the mission follow a Markov chain, and the phase durations are generally distributed. The lifetimes of the non-identical components in the system are assumed to be generally distributed and are modeled using intrinsic aging concepts. Moreover, the lifetime parameters of the components and the configuration of the system change depending on the phases of the mission. We characterize the mean time to failure through solving a Poisson equation, and we analyze the system availability assuming that repair duration has a general distribution which is dependent on the phase of the mission during which the failure has occurred and on the deterioration level of the system.
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    Minimum-variance hedging for managing risks in inventory models with price fluctuations
    (Now Publishers, 2017) N/A; Department of Industrial Engineering; Department of Industrial Engineering; Canyakmaz, Caner; Karaesmen, Fikri; Özekici, Süleyman; PhD Student; Faculty Member; Faculty Member; Department of Industrial Engineering; Graduate School of Sciences and Engineering; College of Engineering; College of Engineering; N/A; 3579; 32631
    We consider the financial hedging of a random operational cash flow that arises in inventory operations with price and demand uncertainty. We use a variance minimization approach to find a financial portfolio that would minimize the total variance of operational and financial returns. For inventory models that involve continuous price fluctuations and price-dependent demand that arrives in continuous time, we characterize the minimum-variance hedging policies and numerically illustrate their effectiveness.
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    Mean-variance newsvendor model with random supply and financial hedging
    (Taylor and Francis Inc, 2015) N/A; Department of Industrial Engineering; Tekin, Müge; Özekici, Süleyman; Master Student; Faculty Member; Department of Industrial Engineering; Graduate School of Sciences and Engineering; College of Engineering; N/A; 32631
    In this paper, we follow a mean-variance (MV) approach to the newsvendor model. Unlike the risk-neutral newsvendor that is mostly adopted in the literature, the MV newsvendor considers the risks in demand as well as supply. We further consider the case where the randomness in demand and supply is correlated with the financial markets. The MV newsvendor hedges demand and supply risks by investing in a portfolio composed of various financial instruments. The problem therefore includes both the determination of the optimal ordering policy and the selection of the optimal portfolio. Our aim is to maximize the hedged MV objective function. We provide explicit characterizations on the structure of the optimal policy. We also present numerical examples to illustrate the effects of risk-aversion on the optimal order quantity and the effects of financial hedging on risk reduction.
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    Optimum component test plans for phased-mission systems
    (Elsevier, 2008) Feyzioğlu, Orhan; Altınel, I. Kuban; Department of Industrial Engineering; Özekici, Süleyman; Faculty Member; Department of Industrial Engineering; College of Engineering; 32631
    We consider the component testing problem of a system that has to perform a mission consisting of a sequence of stages. Once a stage is over, all failed components of the system are replaced before the next stage starts in order to improve its reliability. The components have exponential life distributions where the failure rates depend on the stage of the mission. We formulate the optimal component testing problem as a semi-infinite linear program. We present an algorithmic procedure to compute optimal test times based on the column generation technique and illustrate with numerical examples.
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    Semi-Markov modulated Poisson process: probabilistic and statistical analysis
    (Springer, 2006) Soyer, R.; Department of Industrial Engineering; Özekici, Süleyman; Faculty Member; Department of Industrial Engineering; College of Engineering; 32631
    We consider a Poisson process that is modulated in such a way that the arrival rate at any time depends on the state of a semi-Markov process. This presents an interesting generalization of Poisson processes with important implications in real life applications. Our analysis concentrates on the transient as well as the long term behaviour of the arrival count and the arrival time processes. We discuss probabilistic as well as statistical issues related to various quantities of interest.
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    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; 32631
    N/A
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    Design of optimum component test plans in the demonstration of diverse system performance measures
    (2011) Yamangil, Emre; Altınel, I. Kuban; Feyzioğlu, Orhan; N/A; Department of Industrial Engineering; Çekyay, Bora; Özekici, Süleyman; PhD Student; Faculty Member; Department of Industrial Engineering; Graduate School of Sciences and Engineering; College of Engineering; 110204; 32631
    While component-level tests have many advantages over system-level tests, the actual protection offered in making inferences about system reliability is not the same as what is expected. Thus, a significant proportion of research has concentrated on the design of system-based component test plans that also have minimum cost. This article extends those previous studies by considering two additional system performance measures: expected system lifetime and system availability. After explicitly expressing these performance measures as a function of failure rates for various system types, the component testing problem is formulated as a semi-infinite linear programming problem and solved with a column generation technique incorporating signomial geometric programming. Several numerical examples are presented that provide insight on the model parameters.
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    An EOQ model with multiple suppliers and random capacity
    (Wiley, 2006) Erdem, Aslı Sencer; Fadıloğlu, Mehmet Murat; Department of Industrial Engineering; Özekici, Süleyman; Faculty Member; Department of Industrial Engineering; College of Engineering; 32631
    We consider an EOQ model with multiple suppliers that have random capacities, which leads to uncertain yield in orders. A given order is fully received from a supplier if the order quantity is less than the supplier's capacity; otherwise. the quantity received is equal to the available capacity. The optimal order quantities for the suppliers can be obtained as the unique solution of an implicit set of equations in which the expected unsatisfied order is the same for each supplier. Further characterizations and properties are obtained for the uniform and exponential capacity cases with discussions on the issues related to diversification among suppliers.