Applications – OR and Management Sciences

Metaheuristic, Models and Software for the Heterogeneous Fleet Pickup and Delivery Problem with Split Loads

  • Diogenes Gasque
  • Pedro Munari
    • Categories Meta Heuristics, Optimization Software and Modeling Systems, Transportation Tags , , , ,

    This paper addresses a rich variant of the vehicle routing problem (VRP) that involves pickup and delivery activities, customer time windows, heterogeneous fleet, multiple products and the possibility of splitting a customer demand among several routes. This variant generalizes traditional VRP variants by incorporating features that are commonly found in practice. We present two mixed-integer … Read more

    Joint Routing of Conventional and Range-Extended Electric Vehicles in a Large Metropolitan Network

  • Anirudh Subramanyam
  • Taner Cokyasar
  • Jeffrey Larson
  • Monique Stinson
    • Categories Applications - OR and Management Sciences Tags , , ,

    Range-extended electric vehicles combine the higher efficiency and environmental benefits of battery-powered electric motors with the longer mileage and autonomy of conventional internal combustion engines. This combination is particularly advantageous for time-constrained delivery routing in dense urban areas, where battery recharging along routes can be too time-consuming to economically justify the use of all-electric vehicles. … Read more

    Hub Network Design Problem with Capacity, Congestion and Stochastic Demand Considerations

  • Vedat Bayram
  • Barış Yıldız
  • M. Saleh Farham
    • Categories Second-Order Cone Programming, Stochastic Programming, Transportation Tags , , , , , , ,

    We introduce the hub network design problem with congestion, capacity, and stochastic demand considerations (HNDC), which generalizes the classical hub location problem in several directions. In particular, we extend state-of-the-art by integrating capacity acquisition decision and congestion cost effect into the problem and allowing dynamic routing for origin-destination pairs. Connecting strategic and operational level decisions, … Read more

    Mean-Covariance Robust Risk Measurement

  • Viet Anh Nguyen
  • Soroosh Shafieezadeh-Abadeh
  • Damir Filipovic
  • Daniel Kuhn
    • Categories Finance and Economics, Robust Optimization, Stochastic Programming Tags ,

    We introduce a universal framework for mean-covariance robust risk measurement and portfolio optimization. We model uncertainty in terms of the Gelbrich distance on the mean-covariance space, along with prior structural information about the population distribution. Our approach is related to the theory of optimal transport and exhibits superior statistical and computational properties than existing models. … Read more

    A covering decomposition algorithm for power grid cyber-network segmentation

  • Emma S. Johnson
  • Santanu S. Dey
  • Jonathan Eckstein
  • Cynthia A. Phillips
  • John D. Siirola
    • Categories Applications - OR and Management Sciences Tags , , , , ,

    We present a trilevel interdiction model for optimally segmenting the Supervisory Control and Data Acquisition (SCADA) network controlling an electric power grid. In this formulation, we decide how to partition nodes of the SCADA network in order to minimize the shedding of load from a worst-case cyberattack, assuming that the grid operator has the opportunity … Read more

    Risk-averse Regret Minimization in Multi-stage Stochastic Programs

  • Mehran Poursoltani
  • Erick Delage
  • Angelos Georghiou
    • Categories Applications - OR and Management Sciences, Robust Optimization, Stochastic Programming Tags , , ,

    Within the context of optimization under uncertainty, a well-known alternative to minimizing expected value or the worst-case scenario consists in minimizing regret. In a multi-stage stochastic programming setting with a discrete probability distribution, we explore the idea of risk-averse regret minimization, where the benchmark policy can only benefit from foreseeing Delta steps into the future. … Read more

    Multiple-Periods Locally-Facet-Based MIP Formulations for the Unit Commitment Problem

  • Linfeng Yang
  • Shifei Chen
  • Zhaoyang Dong
    • Categories (Mixed) Integer Nonlinear Programming, Applications - OR and Management Sciences, Polyhedra Tags , , , , , , ,

    The thermal unit commitment (UC) problem has historically been formulated as a mixed integer quadratic programming (MIQP), which is difficult to solve efficiently, especially for large-scale systems. The tighter characteristic reduces the search space, therefore, as a natural consequence, significantly reduces the computational burden. In literatures, many tightened formulations for a single unit with parts … Read more

    The Value of Robust Assortment Optimization Under Ranking-based Choice Models

  • Bradley Sturt
    • Categories Marketing, Robust Optimization, Yield Management Tags , ,

    We study a class of robust assortment optimization problems that was proposed by Farias, Jagabathula, and Shah (2013). The goal in these problems is to find an assortment that maximizes a firm’s worst-case expected revenue under all ranking-based choice models that are consistent with the historical sales data generated by the firm’s past assortments. We … Read more

    Robust Concave Utility Maximization over Chance Constraints

  • Shanshan Wang
  • Sanjay Mehrotra
  • Chun Peng
    • Categories Applications - OR and Management Sciences, Robust Optimization, Stochastic Programming Tags , , , , ,

    This paper first studies an expected utility problem with chance constraints and incomplete information on a decision maker’s utility function. The model maximizes the worst-case expected utility of random outcome over a set of concave functions within a novel ambiguity set, while the underlying probability distribution is known. To obtain computationally tractable formulations, we employ … Read more

    Some Strongly Polynomially Solvable Convex Quadratic Programs with Bounded Variables

  • Jong-Shi Pang
  • Shaoning Han
    • Categories Applications - OR and Management Sciences, Nonlinear Optimization, Quadratic Programming Tags , , ,

    This paper begins with a class of convex quadratic programs (QPs) with bounded variables solvable by the parametric principal pivoting algorithm with $\mbox{O}(n^3)$ strongly polynomial complexity, where $n$ is the number of variables of the problem. Extension of the Hessian class is also discussed. Our research is motivated by a recent reference [7] wherein the … Read more