郑州大学计算智能实验室

Computational Intelligence Laboratory

Call for Papers in IEEE CEC 2019 (Competition)


Call for Papers (Competition)

Multimodal Multiobjective optimization (NO. CEC-01)

Competition in IEEE Congress on Evolutionary Computation 2019

http://www.cec2019.org/

Organized by Jing Liang (liangjing@zzu.edu.cn), Boyang Qu and Dunwei Gong

Website: http://www5.zzu.edu.cn/ecilab/info/1036/1163.htm

Scope and Topics

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.

The aim of this special session is to promote the research on MMO and hence motivate researchers to formulate real-world practical problems. Given that the study of multimodal multiobjective optimization (MMO) is still in its emerging stages, although many real-word applications are likely to be amenable to treatment as a MMOP, to date the researchers have ignored such formulations.

This special session is devoted to the novel approaches, algorithms and techniques for solving MMOPs. The main topics of the special session are:

  • 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

    ......

Submission instructions

The results, codes and the description for your algorithm and results need to be submitted to  liangjing@zzu.edu.cn. Please format your results according to the Technical Report "J.J. Liang, B. Y. Qu, D. W. Gong and C.T. Yue, Problem definitions and evaluation criteria for the CEC special session on multimodal multiobjective optimization".

 

Submission deadline

30th April 2019, 23:59 (GMT)