Optimization of Simulated Systems

Hybrid Rebalancing with Dynamic Hubbing for Free-floating Bike Sharing Using Multi-objective Simulation Optimization

  • Hadi Charkhgard
  • Vahid Mahmoodian
  • Yu Zhang
    • Categories Optimization of Simulated Systems, Transportation Tags , , , ,

    For rebalancing problem of free-floating bike sharing systems, we propose dynamic hubbing (i.e. dynamically determining geofencing areas) and hybrid rebalancing (combining user-based and operator-based strategies) and solve the problem with a novel multi-objective simulation optimization approach. Given historical usage data and real-time bike GPS location information, dynamic geofenced areas (hubs) are determined to encourage users … Read more

    Reinforcement Learning via Parametric Cost Function Approximation for Multistage Stochastic Programming

  • Saeed Ghadimi
  • Raymond Perkins
  • Warren B. Powell
    • Categories Applications - OR and Management Sciences, Optimization of Simulated Systems, Stochastic Programming Tags , , , ,

    The most common approaches for solving stochastic resource allocation problems in the research literature is to either use value functions (“dynamic programming”) or scenario trees (“stochastic programming”) to approximate the impact of a decision now on the future. By contrast, common industry practice is to use a deterministic approximation of the future which is easier … 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

    Resilience assessment for interdependent urban infrastructure systems using dynamic network flow models

  • Panagiotis Angeloudis
  • Nils Goldbeck
  • Washington Ochieng
    • Categories Civil and Environmental Engineering, Optimization of Simulated Systems, Transportation

    Critical infrastructure systems in cities are becoming increasingly interdependent, therefore exacerbating the impacts of disruptive events through cascading failures, hindered asset repairs and network congestion. Current resilience assessment methods fall short of fully capturing such interdependency effects as they tend to model asset reliability and network flows separately and often rely on static flow assignment … 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

    A note on using performance and data profiles for training algorithms

  • Margherita Porcelli
  • Philippe L. Toint
    • Categories Nonlinear Optimization, Optimization of Simulated Systems, Optimization Software Benchmark Tags , , ,

    It is shown how to use the performance and data profile benchmarking tools to improve algorithms’ performance. An illustration for the BFO derivative-free optimizer suggests that the obtained gains are potentially significant. Citation ACM Transactions on Mathematical Software, 45:2 (2019), Article 20. Article Download View A note on using performance and data profiles for training … Read more

    The Adaptive Sampling Gradient Method: Optimizing Smooth Functions with an Inexact Oracle

  • Fatemeh Hashemi
  • Raghu Pasupathy
  • Michael Taaffe
    • Categories Nonlinear Optimization, Optimization of Simulated Systems, Stochastic Programming Tags , ,

    Consider settings such as stochastic optimization where a smooth objective function $f$ is unknown but can be estimated with an \emph{inexact oracle} such as quasi-Monte Carlo (QMC) or numerical quadrature. The inexact oracle is assumed to yield function estimates having error that decays with increasing oracle effort. For solving such problems, we present the Adaptive … Read more

    Optimal threshold classification characteristics

  • David Kisets
    • Categories Basic Sciences Applications, Optimization of Simulated Systems Tags , , ,

    This study looks at the application of mathematical concepts of entropy and Fibonacci sequence in creating optimal dimensional relations of classification character. The paper is devoted to optimization of some numerical relations and integers as unified threshold characteristics of classification type, aimed for example at systemic optimizing the measuring information of various processes. The paper … 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