Semih Atakan

Learn More
In this study, we introduce a distribution network design problem that determines the locations and capacities of the relief distribution points in the last mile network, while considering demandand network-related uncertainties in the post-disaster environment. The problem addresses the critical concerns of relief organizations in designing last mile(More)
The vast majority of the machine scheduling literature focuses on deterministic problems, in which all data is known with certainty a priori. This may be a reasonable assumption when the variability in the problem parameters is low. However, as variability in the parameters increases incorporating this uncertainty explicitly into a scheduling model is(More)
In this paper, we present an MIP formulation for the Unit Commitment problem that leads to significant computational time savings and almost-integral solutions when compared to the state-of-the-art formulations in the literature. Using a variety of test instances from the literature, we provide empirical evidence that the polyhedral structure of the new(More)
In this paper, we present the state-transition formulation for the unit commitment problem. This formulation is based on the definition of new decision variables, which, instead of indicating the on/off status of a generator, captures its state transitions between consecutive time periods. We show that this new approach produces a formulation which(More)
Progressive Hedging (PH) is a well-known algorithm for solving multi-stage stochastic convex optimization problems. Most previous extensions of PH for stochastic mixed-integer programs have been implemented without convergence guarantees. In this paper, we present a new framework that shows how PH can be utilized while guaranteeing convergence to globally(More)
  • 1