rbalexan/BenchmarkFunctions.jl

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

BenchmarkFunctions.jl

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

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.