Applications – OR and Management Sciences

An SDP approach for multiperiod mixed 0–1 linear programming models with stochastic dominance constraints for risk management

  • Laureano F. Escudero
  • Dolores Romero Morales
  • Juan F. Monge
    • Categories (Mixed) Integer Linear Programming, Stochastic Programming, Supply Chain Management

    In this paper we consider multiperiod mixed 0–1 linear programming models under uncertainty. We propose a risk averse strategy using stochastic dominance constraints (SDC) induced by mixed-integer linear recourse as the risk measure. The SDC strategy extends the existing literature to the multistage case and includes both first-order and second-order constraints. We propose a stochastic … Read more

    Local Search for Hop-constrained Directed Steiner Tree Problem with Application to UAV-based Multi-target Surveillance

  • Oleg Burdakov
  • Patrick Doherty
  • Jonas Kvarnström
    • Categories Applications - OR and Management Sciences, Multi-Criteria Optimization, Network Optimization Tags , , , ,

    We consider the directed Steiner tree problem (DSTP) with a constraint on the total number of arcs (hops) in the tree. This problem is known to be NP-hard, and therefore, only heuristics can be applied in the case of its large-scale instances. For the hop-constrained DSTP, we propose local search strategies aimed at improving any … Read more

    An Exact Extended Formulation for the Unrelated Parallel Machine Total Weighted Completion Time Problem

  • Kerem Bülbül
  • Halil Sen
    • Categories (Mixed) Integer Linear Programming, Cutting Plane Approaches, Scheduling

    The plethora of research on NP-hard parallel machine scheduling problems is focused on heuristics due to the theoretically and practically challenging nature of these problems. Only a handful of exact approaches are available in the literature, and most of these suffer from scalability issues. Moreover, the majority of the papers on the subject are restricted … Read more

    Binary Decision Rules for Multistage Adaptive Mixed-Integer Optimization

  • Dimitris Bertsimas
  • Angelos Georghiou
    • Categories Applications - OR and Management Sciences, Integer Programming, Robust Optimization Tags , ,

    Decision rules provide a flexible toolbox for solving the computationally demanding, multistage adaptive optimization problems. There is a plethora of real-valued decision rules that are highly scalable and achieve good quality solutions. On the other hand, existing binary decision rule structures tend to produce good quality solutions at the expense of limited scalability, and are … Read more

    Product Assortment Competition with the Decoy Effect

  • Anton J. Kleywegt
  • Xinchang Wang
    • Categories Applications - OR and Management Sciences, Marketing, Yield Management Tags , , , , ,

    The fraction of customers who choose a particular item from among a set of available items can be increased significantly by the inclusion of a related inferior (and apparently irrelevant) item in the choice set. This violation of the independence from irrelevant alternatives and the regularity properties is called the decoy effect, dominance effect, or … Read more

    Fast Projection onto the Simplex and the l1 Ball

  • Laurent Condat
    • Categories Applications - OR and Management Sciences, Convex and Nonsmooth Optimization Tags , ,

    A new algorithm is proposed to project, exactly and in finite time, a vector of arbitrary size onto a simplex or a l1-norm ball. The algorithm is demonstrated to be faster than existing methods. In addition, a wrong statement in a paper by Duchi et al. is corrected and an adversary sequence for Michelot’s algorithm … Read more

    A branch-cut-and-price algorithm for the energy minimization vehicle routing problem

  • Ricardo Fukasawa
  • Qie He
  • Yongjia Song
    • Categories Applications - OR and Management Sciences, Combinatorial Optimization, Integer Programming

    We study a variant of the capacitated vehicle routing problem where the cost over each arc is defined as the product of the arc length and the weight of the vehicle when it traverses that arc. We propose two new mixed integer linear programming formulations for the problem: an arc-load formulation and a set partitioning … Read more

    A hybrid Lagrangean metaheuristic for single machine scheduling problem with sequence-dependent setup times and due dates

  • Carlos Roberto Venâncio de Carvalho
  • Thiago Henrique Nogueira
  • Martín Gómez Ravetti
  • Gabriel Pinheiro Alves Santos
    • Categories Meta Heuristics, Scheduling Tags , , , ,

    In this article, a hybrid Lagrangean metaheuristic is proposed for single machine scheduling problems with sequence-dependent setup times and due dates. The objective function considered throughout this work, is to minimize the total tardiness. Related works and taxonomies for hybrid metaheuristics are analyzed, through a thorough historical overview. The proposed hybrid Lagrangean metaheuristic is a … Read more

    Robust risk adjustment in health insurance

  • Aurelie Thiele
  • Tengjiao Xiao
    • Categories Applications - OR and Management Sciences, Robust Optimization Tags , ,

    Risk adjustment is used to calibrate payments to health plans based on the relative health status of insured populations and helps keep the health insurance market competitive. Current risk adjustment models use parameter estimates obtained via regression and are thus subject to estimation error. This paper discusses the impact of parameter uncertainty on risk scoring, … Read more

    Robust Investment Management with Uncertainty in Fund Managers’ Asset Allocation

  • Yang Dong
  • Aurelie Thiele
    • Categories Finance and Economics, Robust Optimization Tags , ,

    We consider a problem where an investment manager must allocate an available budget among a set of fund managers, whose asset allocations are not precisely known to the investment manager. In this paper, we propose a robust framework that takes into account the uncertainty stemming from the fund managers’ allocation, as well as the more … Read more