no code implementations • 2 Jun 2019 • Zhun Fan, Zhaojun Wang, Wenji Li, Yutong Yuan, Yugen You, Zhi Yang, Fuzan Sun, Jie Ruan, Zhaocheng Li
In dealing with constrained multi-objective optimization problems (CMOPs), a key issue of multi-objective evolutionary algorithms (MOEAs) is to balance the convergence and diversity of working populations.
no code implementations • 27 Jul 2017 • Zhun Fan, Wenji Li, Xinye Cai, Han Huang, Yi Fang, Yugen You, Jiajie Mo, Caimin Wei, Erik Goodman
In order to evaluate the performance of MOEA/D-IEpsilon, a new set of CMOPs with two and three objectives is designed, having large infeasible regions (relative to the feasible regions), and they are called LIR-CMOPs.