IEEE CEC'2017 Competition on Evolutionary Many-Objective Optimization

2017 IEEE Congress on Evolutionary Computation Donostia - San Sebastián, Spain June 5-8, 2017

The competition allows participants to run their own algorithms on 15 benchmark functions, with a number of 5, 10 and 15 objectives respectively. The purpose of this competition is to make it easier for comparative studies of different algorithms using the same platform. To run the competition, we provide an open-source MATLAB software platform - PlatEMO [1], which is open source and free to use. All the benchmark functions and experimental settings are embedded in PlatEMO. Participants can conduct simulations via a user-friendly GUI, and statistical results of the performance metrics can be directly generated by the software platform in the form of LaTex or Excel files. Details of the set of the test functions and experimental setups are available in a Technical Report [2]. Interested participants are welcome to report their approaches and results in a paper submitted to the submission system of CEC'2017. Or alternatively, the results can be submitted in the form of a brief technical report, which should be sent directly to Ran Cheng or Miqing Li. Submissions in both forms will be considered as entries, therefore be ranked according to the competition evaluation criteria.


Important Dates

An example about including a figure.

For participants planning to submit a paper to the 2017 IEEE Congress on Evolutionary Computation:

For other participants (only result entry but without a paper):

  • Results submission deadline: 1 May 14 May 2017

  • Note: Please send your results directly to Ran Cheng or Miqing Li


1st Place

  • Algorithm: MaOEA-CS (Many-objective evolutionary algorithm based on corner solution search)
  • Participants: Haoran Sun, Chunyang Zhu, Xinye Cai
  • Affiliation: College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, China

2nd Place

  • Algorithm: GSRA (Gradient stochastic ranking algorithm)
  • Participants: Ye Chen, Xiaoping Yuan, Hui Sun, Peng Jin
  • Affiliation: School of Information and Control Engineering, China University of Mining and Technology, China

3rd Place

  • Algorithm: AGE-II (approximation-guided evolution II)
  • Participant: Markus Wagner
  • Affiliation: School of Computer Science, University of Adelaide, Australia


For full results, including source code, data sets and technical reports, please visit our repository.


Ran Cheng
University of Birmingham
United Kingdom

Miqing Li
University of Birmingham
United Kingdom

Ye Tian
Anhui University

Xingyi Zhang
Anhui University

Shengxiang Yang
De Montfort University
United Kingdom

Yaochu Jin
University of Surrey
United Kingdom

Xin Yao
University of Brimginham
United Kingdom