郑州大学计算智能实验室

Computational Intelligence Laboratory

Call for Participants in IEEE CEC 2020 (Special Session & Competition)

 

Call for Participants

Multimodal Multiobjective Optimization (MMO)

Special Session & Competition in IEEE Congress on Evolutionary Computation 2020

(Special Session-No. S17 & Competition-No.CEC-C7)

https://wcci2020.org/

Aim

In multiobjective optimization problems, there may exist two or more distinct Pareto optimal sets (PSs) corresponding to the same Pareto Front (PF). These problems are defined as multimodal multiobjective optimization problems (MMOPs). Arguably, finding one of these multiple PSs may be sufficient to obtain an acceptable solution for some problems. However, failing to identify more than one of the PSs may prevent the decision maker from considering solution options that could bring about improved performance.

A suite of MMOPs were released in CEC 2019. However, the problems with and without local PSs are mixed together and the number of local or global PSs need to be obtained is not specified. In this Special Session & Competition, the problems with and without local PSs are separated and the number of local or global PSs need to be obtained is specified. If several local or global PSs need to be obtained, the population size is increased correspondingly.

The organizers hope that the Special Session & Competition will motivate other researchers to promote the design of novel algorithms to solving MMOPs and the method for MMO test problems.

 

Scope

Topics of interest may cover, but are not limited to

 

- Evolutionary algorithms for multimodal multiobjective optimization

- Hybrid algorithms for multimodal multiobjective optimization

- Adaptable algorithms for multimodal multiobjective optimization

- Surrogate techniques for multimodal multiobjective optimization

- Machine learning methods helping to solve multimodal multiobjective optimization problems

- Memetic computing for multimodal multiobjective optimization

- Niching techniques for multimodal multiobjective optimization

- Parallel computing for multimodal multiobjective optimization

- Design methods for multimodal multiobjective optimization test problems

- Decision making in multimodal multiobjective optimization

- Related theory analysis

- Related Applications

 

Submissions

Paper and Results Submissions

    Papers should be submitted following the instructions at the WCCI  2020 web site. Please select the main research topic as the Special Session on “S17: Special Session Associated with CEC Competitions C1, C2 and C7”. Accepted papers will be included and published in the conference proceedings.

    Submission Deadline: 15 January, 2020

       Submission Deadline: Extended to 30 January, 2020

    Paper Acceptance Notification Date: 15 March 2020

    Information on the format and templates for papers can be found here:

    https://ieee-cis.org/conferences/cec2020/upload.php

 


 

Please test your algorithm on the test problems in "CEC2020 MMO test problems". The results, codes and the description for your algorithm and results need to be submitted to  zzuyuecaitong@163.com. Please format your results according to the Technical Report "J.J. Liang, P. N. Suganthan, B. Y. Qu, D. W. Gong and C.T. Yue, “Problem Definitions and Evaluation Criteria for the CEC 2020 Special Session on Multimodal Multiobjective Optimization”.

Organizers

P. N. Suganthan

Nanyang Technological University, Singapore

Email: epnsugan@ntu.edu.sg


Jing Liang

Zhengzhou University, Zhengzhou, China

Email: liangjing@zzu.edu.cn


Boyang Qu

Zhongyuan University of Technology, Zhengzhou, China

Email: qby1984@hotmail.com


Dunwei Gong

China University of Mining and Technology, Xuzhou, China

Email: dwgong@vip.163.com

 

The codes of CEC2020 MMO test problems can download from https://github.com/P-N-Suganthan/2020-Multimodal-Multi-Objective-Benchmark.


Please participate in the competition with submitting one paper to the Special Session “CEC-14 Special Session on Associated with CEC 2020 Numerical Optimization Competitions”.