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ParMOO: A Python library for parallel multiobjective simulation optimization

Journal Article · · Journal of Open Source Software
DOI:https://doi.org/10.21105/joss.04468· OSTI ID:2001237
 [1];  [2]
  1. Argonne National Laboratory (ANL), Argonne, IL (United States)
  2. Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States); Argonne National Laboratory (ANL), Argonne, IL (United States); Northwestern University, Evanston, IL (United States)
+ Show Author Affiliations

A multiobjective optimization problem (MOOP) is an optimization problem in which multiple objectives are optimized simultaneously. The goal of a MOOP is to find solutions that describe the tradeoff between these (potentially conflicting) objectives. Such a tradeoff surface is called the Pareto front. Real-world MOOPs may also involve constraints – additional hard rules that every solution must adhere to. In a multiobjective simulation optimization problem, the objectives are derived from the outputs of one or more computationally expensive simulations. Such problems are ubiquitous in science and engineering.

Research Organization:
Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
Sponsoring Organization:
USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR)
Grant/Contract Number:
AC02-05CH11231
OSTI ID:
2001237
Journal Information:
Journal of Open Source Software, Journal Name: Journal of Open Source Software Journal Issue: 82 Vol. 8; ISSN 2475-9066
Publisher:
Open Source Initiative - NumFOCUSCopyright Statement
Country of Publication:
United States
Language:
English

References (10)

A multi-objective DIRECT algorithm for ship hull optimization journal October 2017
Parallel strategies for Direct Multisearch journal July 2022
jMetalPy: A Python framework for multi-objective optimization with metaheuristics journal December 2019
Pymoo: Multi-Objective Optimization in Python journal January 2020
PlatEMO: A MATLAB Platform for Evolutionary Multi-Objective Optimization [Educational Forum] journal November 2017
libEnsemble: A Library to Coordinate the Concurrent Evaluation of Dynamic Ensembles of Calculations journal April 2022
Chapter 40: POUNDERS in TAO: Solving Derivative-Free Nonlinear Least-Squares Problems with POUNDERS book April 2017
Algorithm 1028: VTMOP: Solver for Blackbox Multiobjective Optimization Problems journal September 2022
PyMOSO: Software for Multiobjective Simulation Optimization with R-PERLE and R-MinRLE journal April 2020
A parallel global multiobjective framework for optimization: pagmo journal September 2020

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Related Subjects

97 MATHEMATICS AND COMPUTING