Optimization of Simulated Systems

Simulation Optimization for the Stochastic Economic Lot Scheduling Problem with Sequence-Dependent Setup Times

  • Nils Löhndorf
  • Stefan Minner
  • Manuel Riel
    • Categories Optimization of Simulated Systems, Scheduling, Stochastic Approaches Tags , , , , ,

    We consider the stochastic economic lot scheduling problem (SELSP) with lost sales and random demand, where switching between products is subject to sequence-dependent setup times. We propose a solution based on simulation optimization using an iterative two-step procedure which combines global policy search with local search heuristics for the traveling salesman sequencing subproblem. To optimize … Read more

    Do You Trust Derivatives or Differences?

  • Jorge Moré
  • Stefan M. Wild
    • Categories Optimization of Simulated Systems, Optimization Software and Modeling Systems, Optimization Software Design Principles Tags , ,

    We analyze the relationship between the noise level of a function and the accuracy and reliability of derivatives and difference estimates. We derive and empirically validate measures of quality for both derivatives and difference estimates. Using these measures, we quantify the accuracy of derivatives and differences in terms of the noise level of the function. … Read more

    Simulation Optimization for the Stochastic Economic Lot Scheduling Problem

  • Nils Löhndorf
  • Stefan Minner
    • Categories Dynamic Programming, Optimization of Simulated Systems, Scheduling Tags , , , , ,

    We study simulation optimization methods for the stochastic economic lot scheduling problem. In contrast to prior research, we focus on methods that treat this problem as a black box. Based on a large-scale numerical study, we compare approximate dynamic programming with a global search for parameters of simple control policies. We propose two value function … Read more

    Global optimization of expensive black box problems with a known lower bound

  • Andrea Cassioli
  • Fabio Schoen
    • Categories Global Optimization, Optimization of Simulated Systems Tags , , , ,

    In this paper we propose an algorithm for the global optimization of computationally expensive black–box functions. For this class of problems, no information, like e.g. the gradient, can be obtained and function evaluation is highly expensive. In many applications, however, a lower bound on the objective function is known; in this situation we derive a … Read more

    A surrogate management framework using rigorous trust-regions steps

  • Serge Gratton
  • Luis Nunes Vicente
    • Categories Applications - Science and Engineering, Nonlinear Optimization, Optimization of Simulated Systems Tags , , ,

    Surrogate models and heuristics are frequently used in the optimization engineering community as convenient approaches to deal with functions for which evaluations are expensive or noisy, or lack convexity. These methodologies do not typically guarantee any type of convergence under reasonable assumptions and frequently render slow convergence. In this paper we will show how to … Read more

    A surrogate management framework using rigorous trust-regions steps

  • Serge Gratton
    • Categories Applications - Science and Engineering, Nonlinear Optimization, Optimization of Simulated Systems Tags , , ,

    Surrogate models and heuristics are frequently used in the optimization engineering community as convenient approaches to deal with functions for which evaluations are expensive or noisy, or lack convexity. These methodologies do not typically guarantee any type of convergence under reasonable assumptions and frequently render slow convergence. In this paper we will show how to … Read more

    Preconditioning and Globalizing Conjugate Gradients in Dual Space for Quadratically Penalized Nonlinear-Least Squares Problems

  • Serge Gratton
  • Philippe L. Toint
  • Selime Gürol
    • Categories Nonlinear Systems and Least-Squares, Optimization of Simulated Systems, Optimization of Systems modeled by PDEs Tags , , , , ,

    When solving nonlinear least-squares problems, it is often useful to regularize the problem using a quadratic term, a practice which is especially common in applications arising in inverse calculations. A solution method derived from a trust-region Gauss-Newton algorithm is analyzed for such applications, where, contrary to the standard algorithm, the least-squares subproblem solved at each … Read more

    Self-correcting geometry in model-based algorithms for derivative-free unconstrained optimization

  • Katya Scheinberg
  • Philippe L. Toint
    • Categories Optimization of Simulated Systems, Unconstrained Optimization Tags , ,

    Several efficient methods for derivative-free optimization (DFO) are based on the construction and maintenance of an interpolation model for the objective function. Most of these algorithms use special “geometry-improving” iterations, where the geometry (poisedness) of the underlying interpolation set is made better at the cost of one or more function evaluations. We show that such … Read more

    ORBIT: Optimization by Radial Basis Function Interpolation in Trust-Regions

  • Rommel Regis
  • Christine Shoemaker
  • Stefan M. Wild
    • Categories Optimization of Simulated Systems, Unconstrained Optimization Tags , , ,

    We present a new derivative-free algorithm, ORBIT, for unconstrained local optimization of computationally expensive functions. A trust-region framework using interpolating Radial Basis Function (RBF) models is employed. The RBF models considered often allow ORBIT to interpolate nonlinear functions using fewer function evaluations than the polynomial models considered by present techniques. Approximation guarantees are obtained by … Read more