BenchmarkFunctions.jl

A set of common benchmark functions for testing optimization algorithms in Julia
Author rbalexan
Popularity
5 Stars
Updated Last
1 Year Ago
Started In
March 2020

BenchmarkFunctions.jl

A set of common benchmark functions for testing optimization algorithms in Julia

Build Status Coverage Status

Surface and contour plots of the Himmelblau function

Getting Started

To add the package, enter the following into the REPL:

julia> using Pkg
julia> Pkg.add("BenchmarkFunctions")

A simple example for creating a grid and evaluating a benchmark function is:

using BenchmarkFunctions

X = ndgrid(-4:0.1:4,-4:0.1:4)
y = himmelblau(X)

To recreate the above plot:

using BenchmarkFunctions

plot("himmelblau", -4:0.1:4, -4:0.1:4)

Complicated Benchmark Functions

This package also include some complicated benchmark functions.

Real-World Multiobjective Constrained Optimization Problems

The Competition on Real-World Multiobjective Constrained Optimization 2021 (RW-MOP-2021) presented 50 benchmark functions from real-world problems for testing multi-objective optimization algorithms. Those problems are available here.

julia> using BenchmarkFunctions

julia> f, conf = get_RW_MOP_problem(2); # problem 2

julia> conf
Dict{Symbol, Any} with 8 entries:
  :xmin     => [0.05, 0.2, 0.2, 0.35, 3.0]
  :xmax     => [0.5, 0.5, 0.6, 0.5, 6.0]
  :n        => 5
  :function => "vibrating_platform"
  :gn       => 5
  :hn       => 0
  :fn       => 2
  :nadir    => [-0.00127461, 318.255]

Use BenchmarkFunctions.NAME_OF_PROBLEMS_RW_MOP_2021 for full list of problems.

Used By Packages

No packages found.