multi-objective optimization

On implementation details and numerical experiments for the HyPaD algorithm to solve multi-objective mixed-integer convex optimization problems

  • Gabriele Eichfelder
  • Leo Warnow
    • Categories (Mixed) Integer Nonlinear Programming, Multi-Criteria Optimization Tags , ,

    In this paper we present insights on the implementation details of the hybrid patch decomposition algorithm (HyPaD) for convex multi-objective mixed-integer optimization problems. We discuss how to implement the SNIA procedure which is basically a black box algorithm in the original work by Eichfelder and Warnow. In addition, we present and discuss results for various … Read more

    An Upper Bound on the Hausdorff Distance Between a Pareto Set and its Discretization in Bi-Objective Convex Quadratic Optimization

  • Burla E. Ondes
  • Susan R. Hunter
    • Categories Multi-Criteria Optimization, Optimization of Simulated Systems Tags , ,

    We provide upper bounds on the Hausdorff distances between the efficient set and its discretization in the decision space, and between the Pareto set (also called the Pareto front) and its discretization in the objective space, in the context of bi-objective convex quadratic optimization on a compact feasible set. Our results imply that if t … Read more

    An approximation algorithm for multi-objective optimization problems using a box-coverage

  • Gabriele Eichfelder
  • Leo Warnow
    • Categories Global Optimization, Multi-Criteria Optimization Tags , , , ,

    For a continuous multi-objective optimization problem, it is usually not a practical approach to compute all its nondominated points because there are infinitely many of them. For this reason, a typical approach is to compute an approximation of the nondominated set. A common technique for this approach is to generate a polyhedron which contains the … Read more

    Accuracy and fairness trade-offs in machine learning: A stochastic multi-objective approach

  • Suyun Liu
  • Luis Nunes Vicente
    • Categories Data-Mining, Multi-Criteria Optimization, Stochastic Programming Tags , , , , , , , , ,

    In the application of machine learning to real life decision-making systems, e.g., credit scoring and criminal justice, the prediction outcomes might discriminate against people with sensitive attributes, leading to unfairness. The commonly used strategy in fair machine learning is to include fairness as a constraint or a penalization term in the minimization of the prediction … Read more

    The Magic of Nash Social Welfare in Optimization: Do Not Sum, Just Multiply!

  • Hadi Charkhgard
  • Parisa Charkhgard
  • Rasul Esmaeilbeigi
  • Kimia Keshanian
    • Categories Game Theory, Global Optimization, Multi-Criteria Optimization Tags , , , ,

    In this paper, we explain some key challenges when dealing with a single/multi-objective optimization problem in practice. To overcome these challenges, we present a mathematical program that optimizes a Nash Social Welfare function. We refer to this mathematical program as the Nash Social Welfare Program (NSWP). An interesting property of the NSWP is that it … Read more

    Expensive multi-objective optimization of electromagnetic mixing in a liquid metal

  • Thomas Boeck
  • Gabriele Eichfelder
  • Sebastian Prinz
  • Jörg Schumacher
  • Jana Thomann
    • Categories Mechanical Engineering, Multi-Criteria Optimization, Optimization of Simulated Systems Tags , ,

    This paper presents a novel trust-region method for the optimization of multiple expensive functions. We apply this method to a biobjective optimization problem in fluid mechanics, the optimal mixing of particles in a flow in a closed container. The three-dimensional time-dependent flows are driven by Lorentz forces that are generated by an oscillating permanent magnet … Read more

    Objective Selection for Cancer Treatment: An Inverse Optimization Approach

  • Temitayo Ajayi
  • Andrew J. Schaefer
  • Taewoo Lee
    • Categories Biomedical Applications, Convex and Nonsmooth Optimization, Multi-Criteria Optimization Tags , , , , , ,

    In radiation therapy treatment-plan optimization, selecting a set of clinical objectives that are tractable and parsimonious yet effective is a challenging task. In clinical practice, this is typically done by trial and error based on the treatment planner’s subjective assessment, which often makes the planning process inefficient and inconsistent. We develop the objective selection problem … Read more

    Representation of the Pareto front for heterogeneous multi-objective optimization

  • Gabriele Eichfelder
  • Jana Thomann
    • Categories Multi-Criteria Optimization, Unconstrained Optimization Tags , , ,

    Optimization problems with multiple objectives which are expensive, i.e. where function evaluations are time consuming, are difficult to solve. Finding at least one locally optimal solution is already a difficult task. In case only one of the objective functions is expensive while the others are cheap, for instance analytically given, this can be used in … Read more

    The stochastic multi-gradient algorithm for multi-objective optimization and its application to supervised machine learning

  • Suyun Liu
  • Luis Nunes Vicente
    • Categories Convex Optimization, Multi-Criteria Optimization, Stochastic Programming Tags , , ,

    Optimization of conflicting functions is of paramount importance in decision making, and real world applications frequently involve data that is uncertain or unknown, resulting in multi-objective optimization (MOO) problems of stochastic type. We study the stochastic multi-gradient (SMG) method, seen as an extension of the classical stochastic gradient method for single-objective optimization. At each iteration … Read more

    Multi-objective optimization models for many-to-one matching problems

  • Natsumi Shimada
  • Yuichi Takano
  • Natsuki Yamazaki
    • Categories (Mixed) Integer Linear Programming, Finance and Economics Tags , , , ,

    This paper is concerned with many-to-one matching problems for assigning residents to hospitals according to their preferences. The stable matching model aims at finding a stable matching, and the assignment game model involves maximizing the total utility; however, these two objectives are incompatible in general. We also focus on a situation where there are predetermined … Read more