Call for Participants
SS-37 Multimodal Multiobjective Path Planning Optimization
Special Session & Competition in IEEE Congress on Evolutionary Computation 2021
https://cec2021.mini.pw.edu.pl/en
Aim
In multiobjective optimization problems, there may exist two or more global or local Pareto optimal sets (PSs) and some of them may correspond to the same Pareto Front (PF). These problems are defined as multimodal multiobjective optimization problems (MMOPs).
It is necessary to study multimodal multi-objective optimization. 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.
Path planning problem is a typical multimodal multiobjective optimization problem. However, no MMO path planning benchmark problems have been released in public.
In this special session, multiobjective path planning problems with multiple PSs are provided.
This special session is devoted to the novel approaches, algorithms and techniques for solving multimodal multiobjective path planning optimization problems.
Scope
Topics of interest may cover, but are not limited to
- Evolutionary algorithms for multimodal multiobjective path planning optimization problem
- Evolutionary algorithms for multimodal multiobjective optimization
- Hybrid algorithms for multimodal multiobjective path planning optimization problem
- Adaptable algorithms for multimodal multiobjective path planning optimization problem
- Surrogate techniques for multimodal multiobjective path planning optimization problem
- Machine learning methods helping to solvemultimodal multiobjective path planning optimization problem
- Memetic computing for multimodal multiobjective path planning optimization problem
- Niching techniques for multimodal multiobjective path planning optimization problem
- Parallel computing for multimodal multiobjective path planning optimization problem
- Design methods for multimodal multiobjective optimization test problems
- Decision making in multimodal multiobjective optimization
- Related theory analysis
- Related Applications
Submissions (Results&Paper)
Results
Please test your algorithm on the test problems in "CEC2021 MMOPP". 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, C.T. Yue, G. P. Li, B. Y. Qu, P. N. Suganthan, and K. J. Yu, “Problem Definitions and Evaluation Criteria for the CEC 2021 on Multimodal Multiobjective Path Planning Optimization”. 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://cec2021.mini.pw.edu.pl/en
When submitting papers, please make sure that you select “SS-37 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 2021. 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: 31 January 2021 21 February 2021
Paper Acceptance Notification Date: 22 March 2021
Submissions
Paper and Results Submissions
Submission Deadline: 31 January 2021 21 February 2021
Paper Acceptance Notification Date: 22 March 2021
Organizers
Jing Liang
Zhengzhou University, Zhengzhou, China
Email: liangjing@zzu.edu.cn
Caitong Yue
Zhengzhou University, Zhengzhou, China
Email: yuecaitong@zzu.edu.cn
Gongping Li
Zhengzhou University, Zhengzhou, China
Email: ligongping361@163.com
Boyang Qu
Zhongyuan University of Technology, Zhengzhou, China
Email: qby1984@hotmail.com
P. N. Suganthan
Nanyang Technological University, Singapore
Email: epnsugan@ntu.edu.sg
Kunjie Yu
Zhengzhou University, Zhengzhou, China
Email: yukunjie@zzu.edu.cn