Other Topics

On the Out-of-Sample Performance of Stochastic Dynamic Programming and Model Predictive Control

  • Dominic S. T. Keehan
  • Andrew B. Philpott
  • Edward Anderson
    • Categories Dynamic Programming, Stochastic Programming Tags , , ,

    Sample average approximation–based stochastic dynamic programming (SDP) and model predictive control (MPC) are two different methods for approaching multistage stochastic optimization. In this paper we investigate the conditions under which SDP may be outperformed by MPC. We show that, depending on the presence of concavity or convexity, MPC can be interpreted as solving a mean-constrained … Read more

    Black-box optimization for the design of a jet plate for impingement cooling

  • Filippo Marini
  • Margherita Porcelli
  • Elisa Riccietti
  • Lorenzo Cocchi
    • Categories Applications - Science and Engineering, Optimization of Simulated Systems, Other Topics Tags , , ,

    In this work, we propose a novel black-box formulation of the impingement cooling system for a nozzle in a gas turbine. Leveraging on a well-known model that correlates the design features of the cooling system with the efficiency parameters, we develop NOZZLE, a new constrained black-box optimization formulation for the jet impingement cooling design. Then … Read more

    A Jacobi-type Newton method for Nash equilibrium problems with descent guarantees

  • Oliver Kolossoski
  • Luís Felipe Bueno
  • Gabriel Haeser
    • Categories Game Theory, Nonlinear Optimization, Other Topics Tags , , , ,

    A common strategy for solving an unconstrained two-player Nash equilibrium problem with continuous variables is applying Newton’s method to the system obtained by the corresponding first-order necessary optimality conditions. However, when taking into account the game dynamics, it is not clear what is the goal of each player when considering they are taking their current … Read more

    Data Collaboration Analysis with Orthonormal Basis Selection and Alignment

  • Keiyu Nosaka
  • Yuichi Takano
  • Akiko Yoshise
    • Categories Linear, Cone and Semidefinite Programming, Optimization in Data Science, Other Topics

    Data Collaboration (DC) enables multiple parties to jointly train a model by sharing only linear projections of their private datasets. The core challenge in DC is to align the bases of these projections without revealing each party’s secret basis. While existing theory suggests that any target basis spanning the common subspace should suffice, in practice, … Read more

    Uncertainty Quantification for Multiobjective Stochastic Convex Quadratic Programs

  • Ziyu Liu
  • Susan R. Hunter
  • Nan Kong
  • Raghu Pasupathy
    • Categories Multi-Criteria Optimization, Quadratic Programming, Stochastic Programming

    A multiobjective stochastic convex quadratic program (MOSCQP) is a multiobjective optimization problem with convex quadratic objectives that are observed with stochastic error. MOSCQP is a useful problem formulation arising, for example, in model calibration and nonlinear system identification when a single regression model combines data from multiple distinct sources, resulting in a multiobjective least squares … Read more

    On Coupling Constraints in Linear Bilevel Optimization

  • Dorothee Henke
  • Henri Lefebvre
  • Martin Schmidt
  • Johannes Thürauf
    • Categories (Mixed) Integer Linear Programming, Complementarity and Variational Inequalities, Other Topics Tags ,

    It is well-known that coupling constraints in linear bilevel optimization can lead to disconnected feasible sets, which is not possible without coupling constraints. However, there is no difference between linear bilevel problems with and without coupling constraints w.r.t. their complexity-theoretical hardness. In this note, we prove that, although there is a clear difference between these … Read more

    Solution methods for partial inverse combinatorial optimization problems in which weights can only be increased

  • Eva Ley
  • Maximilian Merkert
    • Categories (Mixed) Integer Linear Programming, Branch and Cut Algorithms, Game Theory Tags , , ,

    Partial inverse combinatorial optimization problems are bilevel optimization problems in which the leader aims to incentivize the follower to include a given set of elements in the solution of their combinatorial problem. If the set of required elements defines a complete follower solution, the inverse combinatorial problem is solvable in polynomial time as soon as … Read more

    Policy with guaranteed risk-adjusted performance for multistage stochastic linear problems

  • Bernardo Freitas Paulo da Costa
  • Vincent Leclère
    • Categories Convex Optimization, Dynamic Programming, Stochastic Programming Tags , , ,

    Risk-averse multi-stage problems and their applications are gaining interest in various fields of applications. Under convexity assumptions, the resolution of these problems can be done with trajectory following dynamic programming algorithms like Stochastic Dual Dynamic Programming (SDDP) to access a deterministic lower bound, and dual SDDP for deterministic upper bounds. In this paper, we leverage … Read more

    A Hybrid Genetic Algorithm for Generalized Order Acceptance and Scheduling

  • Sasan Mahmoudinazlou
  • Hadi Charkhgard
    • Categories Applications - OR and Management Sciences, Dynamic Programming, Scheduling Tags , , ,

    In this paper, a novel approach is presented to address a challenging optimization problem known as Generalized Order Acceptance Scheduling. This problem involves scheduling a set of orders on a single machine with release dates, due dates, deadlines, and sequence-dependent setup times judiciously to maximize revenue. In view of resource constraints, not all orders can … Read more

    Kantorovich and Zalgaller (1951): the 0-th Column Generation Algorithm

  • Eduardo Uchoa
  • Ruslan Sadykov
    • Categories Other Topics Tags , ,

    This article delves into the early development of the Column Generation technique. It begins with Kantorovich’s classic 1939 work, correcting widespread misconceptions about his contributions to the Cutting Stock Problem. Then, it brings to light Kantorovich and Zalgaller’s lesser-known 1951 book, which is revealed to contain a complete Column Generation algorithm. The article also places … Read more