Evolutionary Multitasking for Multiobjective Continuous Optimization: Benchmark Problems, Performance Metrics and Baseline Results

lib:a2a6b79f27849cea (v1.0.0)

Authors: Yuan Yuan,Yew-Soon Ong,Liang Feng,A. K. Qin,Abhishek Gupta,Bingshui Da,Qingfu Zhang,Kay Chen Tan,Yaochu Jin,Hisao Ishibuchi
ArXiv: 1706.02766
Document:  PDF  DOI 
Abstract URL: http://arxiv.org/abs/1706.02766v1

In this report, we suggest nine test problems for multi-task multi-objective optimization (MTMOO), each of which consists of two multiobjective optimization tasks that need to be solved simultaneously. The relationship between tasks varies between different test problems, which would be helpful to have a comprehensive evaluation of the MO-MFO algorithms. It is expected that the proposed test problems will germinate progress the field of the MTMOO research.

Relevant initiatives  

Related knowledge about this paper Reproduced results (crowd-benchmarking and competitions) Artifact and reproducibility checklists Common formats for research projects and shared artifacts Reproducibility initiatives


Please log in to add your comments!
If you notice any inapropriate content that should not be here, please report us as soon as possible and we will try to remove it within 48 hours!