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 : 1.1

Developers : Michael G. Epitropakis and Xiaodong Li

Please refer to:

• https://titan.csit.rmit.edu.au/~e46507/cec13-niching/
• https://titan.csit.rmit.edu.au/~e46507/cec13-niching/competition/

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.

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• About:

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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.

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• Documentation:

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

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• Installation instructions:

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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:

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• Directory Structure:

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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
       |
       +- CEC2013	Project files
       |
       +- data		Data files for the benchmark suite 

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

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-- C/C++:

The c++ folder contains:

+ main.cpp:
|-- 	Examples on how to use each benchmark functions.
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+ cec2013.h cec2013.cpp
|-- 	Interface and implementation of the CEC 2013 competition
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+ cfunction.h cfunction.cpp
|-- 	The implementation of the benchmark function suite.
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+ plots.cpp
|-- 	Source code to produce data files for plotting the benchmark functions
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+ plots/
|-- 	It includes plotting data files, and the benchmark functions' figures. 
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+ plots/plots.m
|-- 	MATLAB script for reproducing 1D/2D plots for the benchmark functions
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+ Makefile: 
|-- 	A simple Makefile for easy compilation. 
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+ data/
|-- 	Folder with data files
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+ rand2.h rand2.c
|-- 	A simple random number generator 
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+ randfile
|-- 	In Linux just a symbolic link on /dev/urandom 
|
+ sortidx.h
|-- 	Help header file for sorting

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• Compilation

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The Makefile provides the following three options: make clean : Cleans all unnecessary files.

make all : Compiles the main.cpp file. To see a demonstration of all benchmark functions, execute ./a.out

make plots : Compiles the plots.cpp file. To produce the necessary data files execute ./plots. It will produce 12 data files in the plots/ folder, one for each benchmark function. To produce the figures just run the plots.m MATLAB script.

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-- Java:

The Java folder contains all necessary files to use the competition function set. Please follow the demonstration file ExampleUsage.java on how to use the source code. To reproduce the figures from the technical report please execute the Plots.java file.

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-- python:

The python folder contains all necessary files to use the competition function set. Please follow the demonstration file demo.py on how to use the source code.

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-- ACKNOWLEDGEMENT:

• We really want to thank Dr. Jerry Swan for his fruitful comments and suggestions that helped to improve, the design and the implementation of the competition in the Java programming language.
• We also thank Dr. Daniel Molina Cabrera, for finding and correcting a bug in the Java source code.
• We also thank Dr. Catalin Stoean, for finding and correcting a bug in the source code.
• We also thank Dr. Mike Preuss, for his valuable help and contributions on the competition.
• We really want to thank Eduardo Nobre Luis, and Fabricio Olivetti de Franca for providing us a first implementation of the competition in python. This version help us to redesign and re-implement the required infrastructure in python.
• We also thank Francesco Fracchia, for finding and correcting the fitness value accuracy for shubert function
• Many thanks to Ali Ahrari, for finding and correcting a bug in the matlab implementation
• Many thanks to Simon Wessing, for finding and correcting a bug in the python implementation
• Many thanks to André L. Maravilha, for finding a bug in the MATLAB implementation

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-- LICENSE

This folder should contain a file with the license statement (LICENSE.txt)

Copyright 2013, Michael G. Epitropakis, Xiaodong Li, and Andries Engelbrecht. All rights reserved.

Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:

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