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

    Mathematical programming approach to tighten a Big-$ formulation

  • Alejandro Crema
    • Categories Integer Programming Tags ,

    In this paper we present a mathematical programming approach to tighten a Big-$M$ formulation ($P_M$) of a Mixed Integer Problem with Logical Implications ($P$). If $M_0$ is a valid vector (the optimal solutions of $P$ belong to the feasible solutions set of $P_{M_0}$) our procedures find a valid vector $M$ such that $M \leq M_0$. … 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

    Homotopy methods based on l0 norm for the compressed sensing problem

  • Zhengshan Dong
  • Wenxing Zhu
    • Categories Combinatorial Optimization

    In this paper, two homotopy methods, which combine the advantage of the homotopy technique with the effectiveness of the iterative hard thresholding method, are presented for solving the compressed sensing problem. Under some mild assumptions, we prove that the limits of the sequences generated by the proposed homotopy methods are feasible solutions of the problem, … Read more

    Multiperiod Multiproduct Advertising Budgeting: Stochastic Optimization Modeling

  • Cesar Beltran-Royo
  • Laureano F. Escudero
  • Huizhen Zhang
    • Categories Marketing Tags , , , ,

    We propose a stochastic optimization model for the Multiperiod Multiproduct Advertising Budgeting problem, so that the expected profit of the advertising investment is maximized. The model is a convex optimization problem that can readily be solved by plain use of standard optimization software. It has been tested for planning a realistic advertising campaign. In our … Read more

    An improved algorithm for L2-Lp minimization problem

  • Dongdong Ge
  • He Rongchuan
  • He Simai
    • Categories Global Optimization Theory, Nonsmooth Optimization, Unconstrained Optimization

    In this paper we consider a class of non-Lipschitz and non-convex minimization problems which generalize the L2−Lp minimization problem. We propose an iterative algorithm that decides the next iteration based on the local convexity/concavity/sparsity of its current position. We show that our algorithm finds an epsilon-KKT point within O(log(1/epsilon)) iterations. The same result is also … Read more

    Optimizing healthcare network design under reference pricing and parameter uncertainty

  • Laurent Alfandari
  • Aurelie Thiele
  • Victoire Denoyel
    • Categories Applications - OR and Management Sciences Tags , , ,

    Healthcare payers are exploring cost-containing policies to steer patients, through qualified information and financial incentives, towards providers offering the best value proposition. With Reference Pricing (RP), a payer or insurer determines a maximum amount paid for a procedure, and patients who select a provider charging more pay the difference. In a Tiered Network (TN), providers … Read more

    A regularized limited-memory BFGS method for unconstrained minimization problems

  • Shinji Sugimoto
  • Nobuo Yamashita
    • Categories Unconstrained Optimization Tags , ,

    The limited-memory BFGS (L-BFGS) algorithm is a popular method of solving large-scale unconstrained minimization problems. Since L-BFGS conducts a line search with the Wolfe condition, it may require many function evaluations for ill-posed problems. To overcome this difficulty, we propose a method that combines L-BFGS with the regularized Newton method. The computational cost for a … Read more

    A Generalization of Benders’ Algorithm for Two-Stage Stochastic Optimization Problems With Mixed Integer Recourse

  • Anahita Hassanzadeh
  • Ted K. Ralphs
    • Categories (Mixed) Integer Linear Programming, Stochastic Programming Tags ,

    We describe a generalization of Benders’ method for solving two-stage stochastic linear optimization problems in which there are both continuous and integer variables in the first and second stages. Benders’ method relies on finding effective lower approximations for the value function of the second-stage problem. In this setting, the value function is a discontinuous, non-convex, … Read more

    On the Value Function of a Mixed Integer Linear Optimization Problem and an Algorithm for its Construction

  • Anahita Hassanzadeh
  • Ted K. Ralphs
    • Categories (Mixed) Integer Linear Programming, Stochastic Programming Tags , , ,

    This paper addresses the value function of a general mixed integer linear optimization problem (MILP). The value function describes the change in optimal objective value as the right-hand side is varied and understanding its structure is central to solving a variety of important classes of optimization problems. We propose a discrete representation of the MILP … Read more