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.

Check my GitHub pages too: https://github.com/P-N-Suganthan?tab=repositories

CEC2022, GECCO2022 Special Session / Competition on Real Parameter Single Objective Bound Constrained Optimization

CEC2021, GECCO’21 Special Session / Competition on Real-World Multiobjective (Constrained) Optimization

CEC2021, GECCO’21 Special Session / Competition on Real Parameter Single Objective Bound Constrained Optimization

CEC2021 Special Session / Competition on Multimodal Multiobjective Path Planning Optimization (copy & paste: http://www5.zzu.edu.cn/ecilab/info/1036/1251.htm )

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 (Primarily composition functions were used)

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

CEC10 Special Session on Niching Introduces novel scalable test problems: B. Y. Qu and P. N. Suganthan, “Novel Multimodal Problems and Differential Evolution with Ensemble of Restricted Tournament Selection”, IEEE Congress on Evolutionary Computation, Barcelona, Spain, July 2010.

CEC11  Competition on Testing Evolutionary Algorithms on Real-world Numerical Optimization Problems

CEC2013 Special Session / Competition  on Real Parameter Single Objective Optimization

CEC2014 Special Session / Competition  on Real Parameter Single Objective Optimization (incorporates expensive function optimization)

CEC2014: Dynamic MOEA Benchmark Problems: Subhodip Biswas, Swagatam Das, P. N. Suganthan and C. A. C Coello, "Evolutionary Multiobjective Optimization in Dynamic Environments: A Set of Novel Benchmark Functions," Proc. CEC 2014, July, Beijing, China.

CEC2015 Special Session / Competition  on Real Parameter Single Objective Optimization (incorporates 3 scenarios)

CEC2016 Special Session / Competition  on Real Parameter Single Objective Optimization (incorporates 4 scenarios)

CEC2017 Special Session / Competition  on Real Parameter Single Objective Optimization (incorporates 3 scenarios)

CEC2018 Special Session / Competition on Real Parameter Single Objective Optimization (incorporates 3 scenarios)

SWEVO (Impact Factor=3.8 in 2017) Special issue on Benchmarking Multi and Many Objective Optimization Algorithms

CEC2019 Special Session / Competition on 100-Digit Challenge on Single Objective Numerical Optimization

GECCO 2019 Competition on Numerical Optimization

CEC2020, GECCO’20 Special Session / Competition on Real-World Single Objective Constrained Optimization

CEC2020, GECCO’20 Special Session / Competition on Real Parameter Multimodal Multi-objective Optimization

Check my GitHub pages too: https://github.com/P-N-Suganthan?tab=repositories