In this report, we suggest nine test problems for multi-task single-objective optimization (MTSOO), each of which consists of two single-objective 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 MFO algorithms. It is expected that the proposed test problems will germinate progress the field of the MTSOO research.
@article{arxiv.1706.03470,
title = {Evolutionary Multitasking for Single-objective Continuous Optimization: Benchmark Problems, Performance Metric, and Baseline Results},
author = {Bingshui Da and Yew-Soon Ong and Liang Feng and A. K. Qin and Abhishek Gupta and Zexuan Zhu and Chuan-Kang Ting and Ke Tang and Xin Yao},
journal= {arXiv preprint arXiv:1706.03470},
year = {2017}
}