stochastic programming

Stochastic Programming Models for a Fleet Sizing and Appointment Scheduling Problem with Random Service and Travel Times

  • Shutian Li
  • Karmel S. Shehadeh
  • Man Yiu Tsang
    • Categories Applications - OR and Management Sciences, Scheduling, Stochastic Programming Tags , , , ,

    We propose a new stochastic mixed-integer linear programming model for a home service fleet sizing and appointment scheduling problem (HFASP) with random service and travel times. Specifically, given a set of providers and a set of geographically distributed customers within a service region, our model solves the following decision problems simultaneously: (i) a fleet sizing … Read more

    Data-Driven Approximation of Contextual Chance-Constrained Stochastic Programs

  • Hamed Rahimian
  • Bernardo K. Pagnoncelli
    • Categories Stochastic Programming Tags , , ,

    Uncertainty in classical stochastic programming models is often described solely by independent random parameters, ignoring their dependence on multidimensional features. We describe a novel contextual chance-constrained programming formulation that incorporates features, and argue that solutions that do not take them into account may not be implementable. Our formulation cannot be solved exactly in most cases, … Read more

    Optimizing Vaccine Distribution in Developing Countries under Natural Disaster Risk

  • Bonn Kleiford Seranilla
  • Nils Löhndorf
    • Categories (Mixed) Integer Linear Programming, Dynamic Programming, Stochastic Programming Tags , , ,

    For many developing countries, COVID-19 vaccination roll-out programs are not only slow but vaccination centers are also exposed to the risk of natural disaster, like flooding, which may slow down vaccination progress even further. Policy-makers in developing countries therefore seek to implement strategies that hedge against distribution risk in order for vaccination campaigns to run … Read more

    Asymptotic Consistency for Nonconvex Risk-Averse Stochastic Optimization with Infinite Dimensional Decision Spaces

  • Johannes Milz
  • Thomas Surowiec
    • Categories Optimization of Systems modeled by PDEs, Stochastic Programming, Systems governed by Differential Equations Optimization Tags , , , , , , ,

    Optimal values and solutions of empirical approximations of stochastic optimization problems can be viewed as statistical estimators of their true values. From this perspective, it is important to understand the asymptotic behavior of these estimators as the sample size goes to infinity, which is both of theoretical as well as practical interest. This area of … 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

    Duality in convex stochastic optimization

  • Teemu Pennanen
  • Ari-Pekka Perkkiö
    • Categories Convex Optimization, Infinite Dimensional Optimization, Stochastic Programming Tags , , ,

    This paper studies duality and optimality conditions in general convex stochastic optimization problems introduced by Rockafellar and Wets in \cite{rw76}. We derive an explicit dual problem in terms of two dual variables, one of which is the shadow price of information while the other one gives the marginal cost of a perturbation much like in … Read more

    Dynamic programming in convex stochastic optimization

  • Teemu Pennanen
  • Ari-Pekka Perkkiö
    • Categories Stochastic Programming Tags , ,

    This paper studies the dynamic programming principle for general convex stochastic optimization problems introduced by Rockafellar and Wets in the 1970s. We extend the applicability of the theory by relaxing compactness and boundedness assumptions. In the context of financial mathematics, the relaxed assumptions are satisfied under the well-known no-arbitrage condition and the reasonable asymptotic elasticity … Read more

    Operation of an ambulance fleet under uncertainty

  • Victor Hugo Nascimento
  • Vincent Guigues
  • Anton J. Kleywegt
    • Categories Applications - OR and Management Sciences, Stochastic Programming Tags , , , ,

    We introduce two new optimization models for the dispatch of ambulances. These models are to our knowledge the first providing a full modelling of the operation of an ambulance fleet, taking into account all or almost all constraints of the problem. The first model, called the ambulance selection problem, is used when an emergency call … Read more

    Exact Solutions to a Carsharing Pricing and Relocation Problem under Uncertainty

  • Giovanni Pantuso
    • Categories Stochastic Programming, Transportation Tags , ,

    In this article we study the problem of jointly deciding carsharing prices and vehicle relocations. We consider carsharing services operating in the context of multi-modal urban transportation systems. Pricing decisions take into account the availability of alternative transport modes, and customer preferences with respect to these. In order to account for the inherent uncertainty in … Read more

    Non-anticipative risk-averse analysis with effective scenarios applied to long-term hydrothermal scheduling

  • Karla Cristiane Arsie
  • Clóvis Caesar Gonzaga
  • Elizabeth Wegner Karas
  • Gislaine Aparecida Periçaro
    • Categories Nonlinear Optimization, Stochastic Programming Tags , , ,

    In this paper, we deal with long-term operation planning problems of hydrothermal power systems by considering scenario analysis and risk aversion. This is a stochastic sequential decision problem whose solution must be non-anticipative, in the sense that a decision at a stage cannot use a perfect knowledge of the future. We propose strategies to reduce … Read more