Year: 2022

Chance constrained nonlinear optimization with skewed distributions and dependent rows

  • Jia Liu
  • Shen Peng
  • Abdel Lisser
    • Categories Stochastic Programming Tags , , , ,

    This paper discusses chance constrained optimization problems where the constraints are linear to the random variables but nonlinear to the decision variables. For the individual nonlinear chance constraint, we derive tractable reformulation under finite Gaussian mixture distributions and design tight approximation under the generalized hyperbolic distribution. For the joint nonlinear chance constraint, we study several … Read more

    A Trust Region Method for the Optimization of Noisy Functions

  • Shigeng Sun
  • Jorge Nocedal
    • Categories Nonlinear Optimization Tags , ,

    Classical trust region methods were designed to solve problems in which function and gradient information are exact. This paper considers the case when there are bounded errors (or noise) in the above computations and proposes a simple modification of the trust region method to cope with these errors. The new algorithm only requires information about … Read more

    Time-series aggregation for the optimization of energy systems: goals, challenges, approaches, and opportunities

  • Holger Teichgraeber
  • Adam R. Brandt
    • Categories Data-Mining, Energy, Facility Planning and Design Tags , , , , ,

    The rising significance of renewable energy increases the importance of representing time-varying input data in energy system optimization studies. Time-series aggregation, which reduces temporal model complexity, has emerged in recent years to address this challenge. We provide a comprehensive review of time-series aggregation for the optimization of energy systems. We show where time series affect … Read more

    On the convex hull of convex quadratic optimization problems with indicators

  • Linchuan Wei
  • Alper Atamturk
  • Andrés Gómez
  • Simge Küçükyavuz
    • Categories (Mixed) Integer Nonlinear Programming Tags , ,

    We consider the convex quadratic optimization problem with indicator variables and arbitrary constraints on the indicators. We show that a convex hull description of the associated mixed-integer set in an extended space with a quadratic number of additional variables consists of a single positive semidefinite constraint (explicitly stated) and linear constraints. In particular, convexification of … Read more

    An Algorithm for Stochastic Convex-Concave Fractional Programs with Applications to Production Efficiency and Equitable Resource Allocation

  • Cheolmin Kim
  • Sanjay Mehrotra
    • Categories Global Optimization, Global Optimization Applications, Stochastic Approaches Tags , , , ,

    We propose an algorithm to solve convex and concave fractional programs and their stochastic counterparts in a common framework. Our approach is based on a novel reformulation that involves differences of square terms in the constraints, and subsequent employment of piecewise-linear approximations of the concave terms. Using the branch-and-bound (B&B) framework, our algorithm adaptively refines … Read more

    Absolute regret of implicitly defined sets for combinatorial optimization problems

  • Alejandro Crema
    • Categories Robust Optimization Tags , , ,

    We consider combinatorial optimization problems with interval uncertainty in the cost vector. Recently a new approach was developed to deal with such uncertainties: instead of a single one absolute robust solution, obtained by solving a min max problem, a set of cardinality predefined and minimal absolute regret, obtained by solving a min max min problem, … Read more