This competition is supported by the newly established IEEE CIS Task force on Multi-modal Optimization
This competition is organized in association with the 2017 IEEE CEC Special Session on Niching Methods for Multimodal Optimization. The aim of the competition is to provide a common platform that encourages fair and easy comparisons across different niching algorithms. The competition allows participants to run their own niching algorithms on 20 benchmark multimodal functions with different characteristics and levels of difficulty. Researchers are welcome to evaluate their niching algorithms using this benchmark suite, and report the results by submitting a paper to the associated niching special session (i.e., submitting via the online submission system of CEC'2017).
In case it is too late to submit the paper (i.e., passing the CEC'2017 submission deadline), author may submit their results in a report directly to the special session organizer Michael Epitropakis, in order to be counted in the competition. In addition, the authors are also expected to submit the solutions found in a separate report, in order for us to validate the results.
Test suite for the competition as well as the performance measures are implemented in
Matlab, python, Java, and C/C++, and available for download here or from GitHub. Please refer to the following technical report for more information about these benchmark functions:
Reference: 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.
To those who may participate in the competition: Please inform Michael Epitropakis about your participation, so that we can update you about any correction of bugs or extension of the deadline.
