Algorithm 1028: VTMOP: Solver for Blackbox Multiobjective Optimization Problems

Author:

Chang Tyler H.1ORCID,Watson Layne T.2ORCID,Larson Jeffrey3ORCID,Neveu Nicole4ORCID,Thacker William I.5ORCID,Deshpande Shubhangi6ORCID,Lux Thomas C. H.7ORCID

Affiliation:

1. Virginia Polytechnic Institute and State University, Dept. of Computer Science and Argonne National Laboratory, Mathematics and Computer Science Division, Lemont

2. Virginia Polytechnic Institute and State University, Depts. of Computer Science, Mathematics, and Aerospace and Ocean Engineering, Blacksburg, VA

3. Argonne National Laboratory, Mathematics and Computer Science Division, Lemont

4. SLAC National Accelerator Laboratory, Menlo Park, CA

5. Winthrop University, Rock Hill, SC

6. Oracle Labs, Belmont, CA

7. Virginia Polytechnic Institute and State University, Dept. of Computer Science, Blacksburg, VA

Abstract

VTMOP is a Fortran 2008 software package containing two Fortran modules for solving computationally expensive bound-constrained blackbox multiobjective optimization problems. VTMOP implements the algorithm of [ 32 ], which handles two or more objectives, does not require any derivatives, and produces well-distributed points over the Pareto front. The first module contains a general framework for solving multiobjective optimization problems by combining response surface methodology, trust region methodology, and an adaptive weighting scheme. The second module features a driver subroutine that implements this framework when the objective functions can be wrapped as a Fortran subroutine. Support is provided for both serial and parallel execution paradigms, and VTMOP is demonstrated on several test problems as well as one real-world problem in the area of particle accelerator optimization.

Funder

NSF

U.S. Department of Energy, Office of Science through the Exascale Computing Project

Office of Basic Energy Sciences

Office of Advanced Scientific Computing Research, Scientific Discovery through Advanced Computing (SciDAC) Program

U.S. Dept. of Energy, Office of Science Graduate Student Research program

Oak Ridge Institute for Science and Education

ORAU

Publisher

Association for Computing Machinery (ACM)

Subject

Applied Mathematics,Software

Reference67 articles.

1. A. Adelmann P. Calvo M. Frey A. Gsell U. Locans C. Metzger-Kraus N. Neveu C. Rogers S. Russell S. Sheehy J. Snuverink and D. Winklehner. 2019. OPAL a versatile tool for charged particle accelerator simulations.

2. A. Al-Dujaili and S. Suresh. 2016. A MATLAB toolbox for surrogate-assisted multi-objective optimization: A preliminary study. In Proceedings of the Genetic and Evolutionary Computation Conference. ACM, 1209–1216.

3. Algorithm 1007

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