Other Topics

On generalized-convex constrained multi-objective optimization

  • Christian Günther
  • Christiane Tammer
    • Categories Constrained Nonlinear Optimization, Generalized Convexity/Monoticity, Multi-Criteria Optimization Tags , , , , ,

    In this paper, we consider multi-objective optimization problems involving not necessarily convex constraints and componentwise generalized-convex (e.g., semi-strictly quasi-convex, quasi-convex, or explicitly quasi-convex) vector-valued objective functions that are acting between a real linear topological pre-image space and a finite dimensional image space. For these multi-objective optimization problems, we show that the set of (strictly, weakly) … Read more

    A hybrid approach for Bi-Objective Optimization

  • Kim Allan Andersen
  • Thomas R. Stidsen
    • Categories (Mixed) Integer Linear Programming, Cutting Plane Approaches, Multi-Criteria Optimization

    A large number of the real world planning problems which are today solved using Operations Research methods are actually multi-objective planning problems, but most of them are solved using single-objective methods. The reason for converting, i.e. simplifying, multi- objective problems to single-objective problems is that no standard multi-objective solvers exist and specialized algorithms need to … Read more

    An Introduction to Multi-Objective Simulation Optimization

  • Eric A. Applegate
  • Kyle Cooper
  • Susan R. Hunter
  • Oscar Rincon-Guevara
  • Carolina Vivas-Valencia
  • Viplove Arora
  • Bryan Chong
    • Categories Multi-Criteria Optimization, Optimization of Simulated Systems Tags

    The multi-objective simulation optimization (MOSO) problem is a nonlinear multi-objective optimization problem in which multiple simultaneous and conflicting objective functions can only be observed with stochastic error. We provide an introduction to MOSO at the advanced tutorial level, aimed at researchers and practitioners who wish to begin working in this emerging area. Our focus is … Read more

    From Infinite to Finite Programs: Explicit Error Bounds with Applications to Approximate Dynamic Programming

  • Daniel Kuhn
  • Tobias Sutter
  • John Lygeros
  • Peyman Mohajerin Esfahani
    • Categories Dynamic Programming, Infinite Dimensional Optimization, Stochastic Programming Tags , , , ,

    We consider linear programming (LP) problems in infinite dimensional spaces that are in general computationally intractable. Under suitable assumptions, we develop an approximation bridge from the infinite-dimensional LP to tractable finite convex programs in which the performance of the approximation is quantified explicitly. To this end, we adopt the recent developments in two areas of … Read more

    Dynamic programming algorithms, efficient solution of the LP-relaxation and approximation schemes for the Penalized Knapsack Problem

  • Federico Della Croce
  • Ulrich Pferschy
  • Rosario Scatamacchia
    • Categories 0-1 Programming, Combinatorial Optimization, Dynamic Programming Tags , , ,

    We consider the 0-1 Penalized Knapsack Problem (PKP). Each item has a profit, a weight and a penalty and the goal is to maximize the sum of the profits minus the greatest penalty value of the items included in a solution. We propose an exact approach relying on a procedure which narrows the relevant range … Read more

    A Condensing Algorithm for Nonlinear MPC with a Quadratic Runtime in Horizon Length

  • Joel A E Andersson
  • Moritz Diehl
  • Janick V Frasch
  • Milan Vukov
    • Categories Optimization of Simulated Systems, Quadratic Programming Tags , , , ,

    A large number of practical algorithms for Optimal Control Problems (OCP) relies on a so-called condensing procedure to exploit the given structure in the quadratic programming (QP) subproblems. While the established structure-exploiting condensing algorithm is of cubic complexity in the horizon length, in this technical note we propose a novel algorithm that is only of … Read more

    Regularized Stochastic Dual Dynamic Programming for convex nonlinear optimization problems

  • Vincent Guigues
  • Miguel A. Lejeune
  • Wajdi Tekaya
    • Categories Dynamic Programming, Finance and Economics, Stochastic Programming Tags , , , ,

    We define a regularized variant of the Dual Dynamic Programming algorithm called REDDP (REgularized Dual Dynamic Programming) to solve nonlinear dynamic programming equations. We extend the algorithm to solve nonlinear stochastic dynamic programming equations. The corresponding algorithm, called SDDP-REG, can be seen as an extension of a regularization of the Stochastic Dual Dynamic Programming (SDDP) … Read more

    Understanding Deep Neural Networks with Rectified Linear Units

  • Raman Arora
  • Amitabh Basu
  • Poorya Mianjy
  • Anirbit Mukherjee
    • Categories Applications - Science and Engineering, Other Topics, Polyhedra

    In this paper we investigate the family of functions representable by deep neural networks (DNN) with rectified linear units (ReLU). We give the first-ever polynomial time (in the size of data) algorithm to train a ReLU DNN with one hidden layer to {\em global optimality}. This follows from our complete characterization of the ReLU DNN … Read more

    Second-order cone programming formulation for two player zero-sum game with chance constraints

  • Abdel Lisser
  • Vikas Vikram Singh
    • Categories Game Theory, Stochastic Programming Tags , , , ,

    We consider a two player finite strategic zero-sum game where each player has stochastic linear constraints. We formulate the stochastic constraints of each player as chance constraints. We show the existence of a saddle point equilibrium if the row vectors of the random matrices, defining the stochastic constraints of each player, are elliptically symmetric distributed … Read more