Call for participants Constrained Multimodal Multiobjective Optimization
Special Session & Competition in IEEE Congress on Evolutionary Computation 2023
Aim
In constrained multiobjective optimization problems, there may exist two or more global or local constrained Pareto optimal sets (CPSs) corresponding to the same constrained Pareto front (CPF). These problems are defined as constrained multimodal multiobjective optimization problems (CMMOPs).
Maybe it is adequate to find one of multiple CPSs to obtain an acceptable solution for some problems. Nonetheless, failing to identify and maintain more than one of the CPSs may prevent the decision maker from considering solution options that could bring about improved performance.
The aim of this special session and Competition is to promote the research on constrained multimodal multiobjective optimization (CMMO) and hence motivate researchers to formulate real-world applications. Given that the study of CMMO is still in its emerging stages, although many real-world applications are likely to be amenable to treatment as a CMMOP, to date the researchers have ignored such formulations.
In this special session and Competition, multiple sets of CMMO test problems of different properties and a location optimization problem with multiple optimal regions are presented.
This competition is devoted to the novel approaches, algorithms, and techniques for solving CMMOPs.
Scope
Topics of interest may cover, but are not limited to:
l Evolutionary algorithms for constrained multimodal multiobjective optimization
l Hybrid algorithms for constrained multimodal multiobjective optimization
l Adaptable algorithms for constrained multimodal multiobjective optimization
l Surrogate techniques for constrained multimodal multiobjective optimization
l Machine learning methods helping to solve constrained multimodal multiobjective optimization problems
l Memetic computing for constrained multimodal multiobjective optimization
l Niching techniques for constrained multimodal multiobjective optimization
l Parallel computing for constrained multimodal multiobjective optimization
l Design methods for constrained multimodal multiobjective optimization test problems
l Decision making in constrained multimodal multiobjective optimization
l Related theory analysis
l Applications
Submissions (Result & Paper)
Results
Please test your algorithm on the test problems in “CEC2023 CMMOP”.
The results, codes, and the description for your algorithm and results need to be submitted to the competition platform provided by SOYOTEC Technologies Corp. We will present an overall analysis and comparison based on these results.
Paper
Authors must strictly follow the manuscript preparation instructions to be given at: https://2023.ieee-cec.org/paper-submission/
When submitting papers, please make sure that you select “Constrained Multimodal Multiobjective Path Planning Optimization” as the "Main Research Topic" for all papers making use of these benchmarks.
We will follow the extended deadlines as determined by CEC 2023. If you require extra time, you can email us ( zzuyuecaitong@163.com).
Accepted papers will be included and published in the conference proceedings.
Submission Deadline: January 13th, 2023 January 27th, 2023
Paper Reviews: March 3rd, 2023 March 17th, 2023
Paper Re-submissions: March 24th, 2023 April 7th, 2023
Paper Final Notification: March 31st, 2023 April 14th, 2023
Print-Ready Manuscripts: April 15th, 2023 April 29th, 2023
Organizers
Jing Liang
Henan Institute of Technology, Xinxiang, China
Email: liangjing@zzu.edu.cn
Caitong Yue
Zhengzhou University, Zhengzhou, China
Email: yuecaitong@zzu.edu.cn
Boyang Qu
Zhongyuan University of Technology, Zhengzhou, China
Email: qby1984@hotmail.com
Kunjie Yu
Zhengzhou University, Zhengzhou, China
Email: yukunjie@zzu.edu.cn
Hongyu Lin
Zhengzhou University, Zhengzhou, China
Email: linhongyuayu@163.com