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Benchmark Functions for CEC'2013 Special Session and Competition on Niching Methods for Multimodal Function Optimization

Organizers : Xiaodong Li, Andries Engelbrecht, and Michael G. Epitropakis

Version : 1.2

Developers : Michael G. Epitropakis and Xiaodong Li

Please refer to:

If you are using any material from the current competition please cite the following work:

X. Li, A. Engelbrecht, and M.G. Epitropakis, ``Benchmark Functions for CEC'2013 Special Session and Competition on Niching Methods for Multimodal Function Optimization'', Technical Report, Evolutionary Computation and Machine Learning Group, RMIT University, Australia, 2013.

  • About:

In this folder you can find all necessary source files for the benchmark suite of the CEC'2013 Special Session and Competition on Niching Methods for Multimodal Function Optimization.

The Test suite for the competition is implemented in MATLAB, JAVA, C/C++ and python.

  • Documentation:

For more information please refer to the Technical Report of the Special Session/Competition

  • Installation instructions:

Please unpack the archive and extract its contents in a folder:

unzip FILENAME.zip cd FILENAME

In the FILENAME folder you will find the following folder structure:

  • Directory Structure:

After unpacking the archive file, you should end up with the following structure:

  ./			The MAIN directory, created when unpacking
   |
   +-- matlab		Source code of the benchmark functions in MATLAB
   |   |
   |   +- figs		Figures of the benchmark functions (for validation)
   |   |
   |   +- data		Data files for the benchmark suite 
   |
   +-- c++		Source code of the benchmark functions in C/C++
   |   |
   |   +- plots		Figures of the benchmark function (for validation)
   |   |
   |   +- data		Data files for the benchmark suite 
   |
   +-- java 	Source code of the benchmark functions in JAVA
   |   |
   |   +- CEC2013	Project files
   |
   +-- python	Source code of the benchmark functions in python (v 2)
   |   |
   |   +- CEC2013	Project files
   |   |
   |   +- data		Data files for the benchmark suite 
   +-- python3	Source code of the benchmark functions in python3
   |   |
   |   +- CEC2013	Project files
   |   |
   |   +- data		Data files for the benchmark suite 
   +-- GECCO-all-results-2016-2019   Scripts for calculating performance measures for the three scenarios of the GECCO competition

-- MATLAB:

The matlab folder contains:

+ niching_func.m
|-- 	The source code of the benchmark functions
|
+ demo_suite.m
|-- 	A demonstration file for using the competition source code 
|
+ count_goptima.m
|-- 	function for counting the number of global optima in a population 
|
+ plots.m
|-- 	MATLAB script for reproducing 1D/2D plots for the benchmark functions
|
+ data/
|-- 	Folder with data files
|
+ figs/
|-- 	Folder with the 1D/2D figures of the benchmark suite
|
+ get_fgoptima.m
|-- 	For each function, get the global's optima fitness value
|
+ get_no_goptima.m
|-- 	For each function, get the amount of known global optima 
|
+ get_rho.m
|-- 	For each function, get the rho value
|
+ get_lb.m
|-- 	For each function, get the lower bounds of the optimization box
|
+ get_ub.m
|-- 	For each function, get the upper bounds of the optimization box
|
+ get_copy_of_goptima.m
|-- 	For each function, get the positions of the global optima

-- C/C++: