Susan R. Hunter

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

    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

    PyMOSO: Software for Multi-Objective Simulation Optimization with R-PERLE and R-MinRLE

  • Kyle Cooper
  • Susan R. Hunter
    • Categories Optimization of Simulated Systems, Optimization Software and Modeling Systems Tags ,

    We present the PyMOSO software package for (1) solving multi-objective simulation optimization (MOSO) problems on integer lattices, and (2) implementing and testing new simulation optimization (SO) algorithms. First, for solving MOSO problems on integer lattices, PyMOSO implements R-PERLE, a state-of-the-art algorithm for two objectives, and R-MinRLE, a competitive benchmark algorithm for three or more objectives. … Read more

    Multi-objective Ranking and Selection: Optimal Sampling Laws and Tractable Approximations via SCORE

  • Eric A. Applegate
  • Guy Feldman
  • Susan R. Hunter
  • Raghu Pasupathy
    • Categories Multi-Criteria Optimization, Optimization of Simulated Systems

    Consider the multi-objective ranking and selection (MORS) problem in which we select the Pareto-optimal set from a finite set of systems evaluated on three or more stochastic objectives. Solving this problem is difficult because we must determine how to allocate a simulation budget among the systems to minimize the probability that any systems are misclassified. … Read more

    Bi-objective Simulation Optimization on Integer Lattices using the Epsilon-Constraint Method in a Retrospective Approximation Framework

  • Kyle Cooper
  • Susan R. Hunter
  • Kalyani Nagaraj
    • Categories Integer Programming, Multi-Criteria Optimization, Optimization of Simulated Systems Tags , ,

    We consider multi-objective simulation optimization (MOSO) problems on integer lattices, that is, nonlinear optimization problems in which multiple simultaneous objective functions can only be observed with stochastic error, e.g., as output from a Monte Carlo simulation model. The solution to a MOSO problem is the efficient set, which is the set of all feasible decision … 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

    SCORE Allocations for Bi-objective Ranking and Selection

  • Guy Feldman
  • Susan R. Hunter
    • Categories Global Optimization, Multi-Criteria Optimization, Stochastic Programming Tags , ,

    The bi-objective R&S problem is a special case of the multi-objective simulation optimization problem in which two conflicting objectives are known only through dependent Monte Carlo estimators, the decision space or number of systems is finite, and each system can be sampled to some extent. The solution to the bi-objective R&S problem is a set … Read more