optproblems

License: BSD License

objective, function, black-box, optimization, benchmark, problem, binary, Dixon, ZDT, DTLZ, WFG, CEC

Description

This package contains a collection of common benchmark problems for black-box optimization. Under the term “black-box problem”, we understand problems for which only little is known about their structure and properties. Such problems usually appear in practice when simulator output or some other complex system with nonlinear behavior is to be optimized.

Contained test problems:

Binary problems OneMax, LeadingOnes, and LeadingOnesTrailingZeros
CEC 2005 collection of single-objective problems
CEC 2007 collection of multiobjective problems
Dixon-Szegö collection for global optimization
DTLZ problems 1-7
Multiple-Peaks Model 2
Walking Fish Group (WFG) toolkit
ZDT collection for multiobjective optimization

Contained real-world problems:

Configuration of a gradient method on test problem
Uniformity optimization of points in the unit hypercube

The infrastructure of this package can also be used to wrap your own (real-world) optimization problems in the problem base class. Reasons to do this may be the following features:

Support for single-objective and multi-objective problems
In general, no assumptions about the search space are made
Evaluations are automatically counted
Can use true parallelism or concurrency via multiprocessing(.dummy)
Provides functionality for checking bound constraints and repairing violations of them in continuous optimization
Optionally: detection and subsequently avoidance of duplicate evaluations

Dependencies

Some modules of this package have additional dependencies on third-party packages. However, these are not enforced during installation not to hinder the utilization of the base module, which will always be free of dependencies.

Module	Dependencies
base	none
binary	none
cec2005	numpy
cec2007	numpy, diversipy
continuous	none
dtlz	diversipy
mpm	numpy
multiobjective	diversipy
realworld	numpy, diversipy
wfg	diversipy
zdt	diversipy