Stochastic Programming

A Stochastic Optimization Approach to Energy-Efficient Underground Timetabling under Uncertain Dwell and Running Times

  • Patrick Gemander
  • Andreas Bärmann
  • Alexander Martin
    • Categories (Mixed) Integer Linear Programming, Stochastic Programming, Transportation Tags , , , , ,

    We consider a problem from the context of energy-efficient underground railway timetabling, in which an existing timetable draft is improved by slightly changing departure and running times. In practice, synchronization between accelerating and braking trains to utilize regenerative braking plays a major role for the energy-efficiency of a timetable. Since deviations from a planned timetable … Read more

    Robust planning of production routing problem in closed-loop supply chain of beverage glass bottles

  • Ali Borumand
  • Ahmadreza Marandi
  • Ali Nookabadi
  • Zümbül Atan
    • Categories Robust Optimization, Stochastic Programming, Supply Chain Management Tags , , , ,

    Closed-loop supply chains (CLSC) integrate forward and reverse flows of products and information. This integration helps companies to manage their supply chains better as they have more control and a broader view of the whole chain. Also, companies can have economic and environmental benefits from the returned products. Despite these advantages, managing CLSCs can be … Read more

    A Survey on Bilevel Optimization Under Uncertainty

  • Yasmine Beck
  • Ivana Ljubić
  • Martin Schmidt
    • Categories Global Optimization, Robust Optimization, Stochastic Programming Tags , , ,

    Bilevel optimization is a very active field of applied mathematics. The main reason is that bilevel optimization problems can serve as a powerful tool for modeling hierarchical decision making processes. This ability, however, also makes the resulting problems challenging to solve—both in theory and practice. Fortunately, there have been significant algorithmic advances in the field … Read more

    Planning of Container Crossdocking for an Express Shipment Service Network

  • Anton J. Kleywegt
  • Haotian Wu
    • Categories Applications - OR and Management Sciences, Stochastic Programming, Transportation Tags , , , ,

    In air transportation, container crossdocking refers to a loaded container that is transferred at an airport from an incoming flight to an outgoing flight without handling the freight on the container. It reduces handling time and handling cost relative to unloading the container and sorting the freight, and is an economical alternative if a sufficient … Read more

    Convergence of Trajectory Following Dynamic Programming algorithms for multistage stochastic problems without finite support assumptions

  • Maël Forcier
  • Vincent Leclère
    • Categories Dynamic Programming, Stochastic Programming Tags , ,

    We introduce a class of algorithms, called Trajectory Following Dynamic Programming (TFDP) algorithms, that iteratively refines approximation of cost-to-go functions of multistage stochastic problems with independent random variables. This framework encompasses most variants of the Stochastic Dual Dynamic Programming algorithm. Leveraging a Lipschitz assumption on the expected cost-to-go functions, we provide a new convergence and … Read more

    Dual solutions in convex stochastic optimization

  • Teemu Pennanen
  • Ari-Pekka Perkkiö
    • Categories Control Applications, Finance and Economics, Stochastic Programming Tags , , ,

    This paper studies duality and optimality conditions for general convex stochastic optimization problems. The main result gives sufficient conditions for the absence of a duality gap and the existence of dual solutions in a locally convex space of random variables. It implies, in particular, the necessity of scenario-wise optimality conditions that are behind many fundamental … Read more

    Metrizing Fairness

  • Yves Rychener
  • Bahar Tașkesen
  • Daniel Kuhn
    • Categories Statistics, Stochastic Programming, Unconstrained Optimization Tags , , , , ,

    We study supervised learning problems for predicting properties of individuals who belong to one of two demographic groups, and we seek predictors that are fair according to statistical parity. This means that the distributions of the predictions within the two groups should be close with respect to the Kolmogorov distance, and fairness is achieved by … Read more

    Adjusted Distributionally Robust Bounds on Expected Loss Functions

  • Yasemin Merzifonluoğlu
  • Joseph Geunes
    • Categories Production and Logistics, Robust Optimization, Stochastic Programming Tags , , , ,

    Optimization problems in operations and finance often include a cost that is proportional to the expected amount by which a random variable exceeds some fixed quantity, known as the expected loss function. Representation of this function often leads to computational challenges, depending on the distribution of the random variable of interest. Moreover, in practice, a … Read more

    Neur2SP: Neural Two-stage Stochastic Programming

  • Justin Dumouchelle
  • Rahul Patel
  • Elias B. Khalil
  • Merve Bodur
    • Categories Stochastic Programming Tags , ,

    Stochastic programming is a powerful modeling framework for decision-making under uncertainty. In this work, we tackle two-stage stochastic programs (2SPs), the most widely applied and studied class of stochastic programming models. Solving 2SPs exactly requires evaluation of an expected value function that is computationally intractable. Additionally, having a mixed-integer linear program (MIP) or a nonlinear … Read more

    Conditional Distributionally Robust Functionals

  • Alexander Shapiro
  • Alois Pichler
    • Categories Stochastic Programming Tags , , , ,

    Risk measures incorporate a conservative or risk averse perspective in decisionmaking under uncertainty. Taking a variety of models for the potential outcomes into account, the distributionally robust decision is the most conservative decision among the decisions available. This paper investigates different versions of conditional risk measures and distributionally robust functionals in a multistage setting. The … Read more