Given that the study of multimodal multiobjective optimization (MMO) is still in its emerging stages, although a few MMO algorithms have been proposed, there is still no public test function platform to compare these algorithms.
The organizers hope that the special session 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
- Applications
Submissions
Papers should be submitted following the instructions at the IEEE CEC 2019 web site. Please select the main research topic as the Special Session on “multimodal multiobjective optimization”. Accepted papers will be included and published in the conference proceedings.
- Deadline: 7th January, 2019
- Notification: 7th March 2019
Information on the format and templates for papers can be found here: http://www.cec2019.org/papers.html#templates
The attachment 'Parts of MMO test problems.zip' includes some of the MMO test problems. More MMO test problems and performance indicators will be given in the near future. Please pay close attention to our updating information.
Organizers
Dr. Jing Liang
Professor, Zhengzhou University, Zhengzhou, China
liangjing@zzu.edu.cn
Dr. Boyang Qu
Associate Professor, Zhongyuan University of Technology, Zhengzhou, China
Email: qby1984@hotmail.com
Dr. Dunwei Gong
Professor, China University of Mining and Technology, Xuzhou, China
dwgong@vip.163.com
Further information: http://www5.zzu.edu.cn/ecilab/info/1036/1163.htm
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