Robust Optimization

Dual Decomposition of Two-Stage Distributionally Robust Mixed-Integer Programming under the Wasserstein Ambiguity Set

  • Kibaek Kim
    • Categories (Mixed) Integer Linear Programming, Robust Optimization, Stochastic Programming Tags , ,

    We develop a dual decomposition of two-stage distributionally robust mixed-integer programming (DRMIP) under the Wasserstein ambiguity set. The dual decomposition is based on the Lagrangian dual of DRMIP, which results from the Lagrangian relaxation of the nonanticipativity constraints and min-max inequality. We present two Lagrangian dual problem formulations, each of which is based on different principle. We show … Read more

    Distributionally Robust Optimization Approaches for a Stochastic Mobile Facility Routing and Scheduling Problem

  • Karmel S. Shehadeh
    • Categories (Mixed) Integer Linear Programming, Facility Planning and Design, Robust Optimization Tags , , , ,

    We study a mobile facility (MF) routing and scheduling problem in which probability distributions of the time-dependent demand for MF services is unknown. To address distributional ambiguity, we propose and analyze two distributionally robust MF routing and scheduling (DMFRS) models that seek to minimize the fixed cost of establishing the MF fleet and maximum expected … Read more

    Distributionally Robust Optimization under Distorted Expectations

  • Jun Cai
  • Jonathan Yu-Meng Li
  • Tiantian Mao
    • Categories Applications - OR and Management Sciences, Robust Optimization, Stochastic Programming Tags , , ,

    Distributionally robust optimization (DRO) has arose as an important paradigm to address the issue of distributional ambiguity in decision optimization. In its standard form, DRO seeks an optimal solution against the worst-possible expected value evaluated based on a set of candidate distributions. In the case where a decision maker is not risk neutral, the most … Read more

    The Value of Randomized Strategies in Distributionally Robust Risk Averse Network Interdiction Games

  • Erick Delage
  • Utsav Sadana
    • Categories Applications - OR and Management Sciences, Game Theory, Robust Optimization Tags , , ,

    Conditional Value at Risk (CVaR) is widely used to account for the preferences of a risk-averse agent in the extreme loss scenarios. To study the effectiveness of randomization in interdiction games with an interdictor that is both risk and ambiguity averse, we introduce a distributionally robust network interdiction game where the interdictor randomizes over the … Read more

    Multistage Distributionally Robust Mixed-Integer Programming with Decision-Dependent Moment-Based Ambiguity Sets

  • Siqian Shen
  • Xian Yu
    • Categories (Mixed) Integer Nonlinear Programming, Robust Optimization, Stochastic Programming Tags , , , ,

    We study multistage distributionally robust mixed-integer programs under endogenous uncertainty, where the probability distribution of stage-wise uncertainty depends on the decisions made in previous stages. We first consider two ambiguity sets defined by decision-dependent bounds on the first and second moments of uncertain parameters and by mean and covariance matrix that exactly match decision-dependent empirical … Read more

    Robust Active Preference Elicitation

  • Phebe Vayanos
  • Yingxiao Ye
  • Duncan McElfresh
  • John P. Dickerson
  • Eric Rice
    • Categories Applications - OR and Management Sciences, Robust Optimization

    We study the problem of strategically eliciting the preferences of a decision-maker through a moderate number of pairwise comparison queries with the goal of making them a high quality recommendation for a specific decision-making problem. We are particularly motivated by applications in high stakes domains, such as when choosing a policy for allocating scarce resources … Read more

    A Robust Rolling Horizon Framework for Empty Repositioning

  • Ilke Bakir
  • Alan L. Erera
  • Martin Savelsbergh
    • Categories Network Optimization, Robust Optimization, Transportation

    Naturally imbalanced freight flows force consolidation carriers to reposition resources empty. When constructing empty repositioning plans, the cost of repositioning resources empty needs to be weighed against the cost of corrective actions in case of unavailable resources. This is especially challenging given the uncertainty of future demand. We design and implement a robust rolling horizon … Read more

    Gamma-Robust Electricity Market Equilibrium Models with Transmission and Generation Investments

  • Emre Çelebi
  • Vanessa Krebs
  • Martin Schmidt
    • Categories Applications - OR and Management Sciences, Robust Optimization Tags , , , ,

    We consider uncertain robust electricity market equilibrium problems including transmission and generation investments. Electricity market equilibrium modeling has a long tradition but is, in most of the cases, applied in a deterministic setting in which all data of the model are known. Whereas there exist some literature on stochastic equilibrium problems, the field of robust … Read more

    Equal Risk Pricing and Hedging of Financial Derivatives with Convex Risk Measures

  • Erick Delage
  • Jonathan Yu-Meng Li
  • Saeed Marzban
    • Categories Dynamic Programming, Finance and Economics, Robust Optimization Tags , , , , ,

    In this paper, we consider the problem of equal risk pricing and hedging in which the fair price of an option is the price that exposes both sides of the contract to the same level of risk. Focusing for the first time on the context where risk is measured according to convex risk measures, we … Read more

    Robust location-transportation problems with integer-valued demand

  • Ahmadreza Marandi
  • Geert-Jan van Houtum
  • Abbas Khademi
    • Categories Applications - OR and Management Sciences, Network Optimization, Robust Optimization Tags , , ,

    A location-transportation problem concerns designing a company’s distribution network consisting of one central warehouse with ample stock and multiple local warehouses for a long but finite time horizon. The network is designed to satisfy the demands of geographically dispersed customers for multiple products within given delivery time targets. The company needs to first decide on … Read more