Margaret Wiecek

On Subproblem Tradeoffs in Decomposition and Coordination of Multiobjective Optimization Problems

  • Philip de Castro
  • Margaret Wiecek
    • Categories Multi-Criteria Optimization

    Multiobjective optimization is widely used in applications for modeling and solving complex decision-making problems. To help resolve computational and cognitive difficulties associated with problems which have more than three or four objectives, we propose a decomposition and coordination methodology to support decision making for large multiobjective optimization problems (MOPs) with global, quasi-global, and local variables. … Read more

    On Parametric Linear Programming Duality

  • Benjamin Hamlin
  • Nathan Adelgren
  • Margaret Wiecek
    • Categories Linear Programming, Other Topics Tags , , ,

    Recognizing the strength of parametric optimization to model uncertainty, we extend the classical linear programming duality theory to a parametric setting. For linear programs with parameters in general locations, we prove parametric weak and strong duality theorems and parametric complementary slackness theorems. ArticleDownload

    Pareto Leap: An Algorithm for Biobjective Mixed-Integer Programming

  • Philip de Castro
  • Margaret Wiecek
    • Categories (Mixed) Integer Nonlinear Programming, Integer Programming, Multi-Criteria Optimization Tags , , ,

    Many real-life optimization problems need to make decisions with discrete variables and multiple, conflicting objectives. Due to this need, the ability to solve such problems is an important and active area of research. We present a new algorithm, called Pareto Leap, for identifying the (weak) Pareto slices of biobjective mixed-integer programs (BOMIPs), even when Pareto … Read more

    Decision space decomposition for multiobjective optimization

  • Emma Soriano
  • Margaret Wiecek
  • Mishko Mitkovski
    • Categories Multi-Criteria Optimization Tags , , , ,

    Being inspired by the parametric decomposition theorem for multiobjective optimization problems (MOPs) of Cuenca Mira and Miguel García (2017), and by the block-coordinate descent for single objective optimization problems, we present a decomposition theorem for computing the set of minimal elements of a partially ordered set. This set is decomposed into subsets whose minimal elements … Read more

    A Branch and Bound Algorithm for Biobjective Mixed Integer Quadratic Programs

  • Pubudu L.W. Jayasekara Merenchige
  • Margaret Wiecek
    • Categories (Mixed) Integer Nonlinear Programming, Integer Programming, Multi-Criteria Optimization Tags , , , , ,

    Multiobjective quadratic programs (MOQPs) are appealing since convex quadratic programs have elegant mathematical properties and model important applications. Adding mixed-integer variables extends their applicability while the resulting programs become global optimization problems. We design and implement a branch and bound (BB) algorithm for biobjective mixed-integer quadratic programs (BOMIQPs). In contrast to the existing algorithms in … Read more

    A branch-and-bound algorithm for biobjective mixed-integer programs

  • Pietro Belotti
  • Banu Soylu
  • Margaret Wiecek
    • Categories (Mixed) Integer Linear Programming, Multi-Criteria Optimization Tags , , ,

    We propose a branch-and-bound (BB) algorithm for biobjective mixed-integer linear programs (BOMILPs). Our approach makes no assumption on the type of problem and we prove that it returns all Pareto points of a BOMILP. We discuss two techniques upon which the BB is based: fathoming rules to eliminate those subproblems that are guaranteed not to … Read more

    An Improved Algorithm for Biobjective Integer Programs

  • Ted K. Ralphs
  • Matthew Saltzman
  • Margaret Wiecek
    • Categories Branch and Cut Algorithms, Multi-Criteria Optimization, Problem Solving Environments Tags , , , , , , , ,

    A parametric algorithm for identifying the Pareto set of a biobjective integer program is proposed. The algorithm is based on the weighted Chebyshev (Tchebycheff) scalarization, and its running time is asymptotically optimal. A number of extensions are described, including: a technique for handling weakly dominated outcomes, a Pareto set approximation scheme, and an interactive version … Read more