Benchmarks for Evaluation of Evolutionary Algorithms

We organized several competitions on benchmarking evolutionary algorithms. Recently, we also developed several composition functions to evaluate evolutionary algorithms. The objective of this work is explained in our Swarm Intelligence Symposium 2005 paper and also in the CEC Invited Session / Competition pages listed below.

J. J. Liang, P. N. Suganthan and K. Deb, "Novel Composition Test Functions for Numerical Global Optimization", IEEE Swarm Intelligence Symposium, pp. 68-75, June 2005. Matlab codes of composition functions.

 

CEC'05 Special Session / Competition  on Evolutionary Real Parameter single objective optimization

CEC'06 Special Session / Competition on Evolutionary Constrained Real Parameter single objective optimization

CEC'07 Special Session / Competition on Performance Assessment of real-parameter MOEAs

CEC'08 Special Session / Competition on large scale single objective global optimization with bound constraints

CEC'09 Special Session / Competition on Dynamic Optimization

CEC09 Special Session / Competition on Performance Assessment of real-parameter MOEAs

 

CEC10 Special Session / Competition on large-scale single objective global optimization with bound constraints

 

CEC10 Special Session / Competition on Evolutionary Constrained Real Parameter single objective optimization