no code implementations • 8 Jun 2018 • Xinye Cai, Haoran Sun, Chunyang Zhu, Zhenyu Li, Qingfu Zhang
In this paper, an evolutionary many-objective optimization algorithm based on corner solution search (MaOEA-CS) was proposed.
no code implementations • 10 Feb 2018 • Zhun Fan, Yi Fang, Wenji Li, Xinye Cai, Caimin Wei, Erik Goodman
The experimental results manifest that MOEA/D-ACDP is significantly better than the other four CMOEAs on these test instances and the real-world case, which indicates that ACDP is more effective for solving CMOPs.
no code implementations • 15 Sep 2017 • Zhun Fan, Wenji Li, Xinye Cai, Hui Li, Caimin Wei, Qingfu Zhang, Kalyanmoy Deb, Erik D. Goodman
Compared with other CMOEAs, the proposed PPS method can more efficiently get across infeasible regions and converge to the feasible and non-dominated regions by applying push and pull search strategies at different stages.
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.
no code implementations • 4 Jan 2017 • Zhun Fan, Jiewei Lu, Wenji Li, Caimin Wei, Han Huang, Xinye Cai, Xinjian Chen
In this paper, a hierarchical image matting model is proposed to extract blood vessels from fundus images.
no code implementations • 21 Dec 2016 • Zhun Fan, Wenji Li, Xinye Cai, Hui Li, Caimin Wei, Qingfu Zhang, Kalyanmoy Deb, Erik D. Goodman
Multi-objective evolutionary algorithms (MOEAs) have progressed significantly in recent decades, but most of them are designed to solve unconstrained multi-objective optimization problems.
no code implementations • 1 Apr 2015 • Zhun Fan, Wenji Li, Xinye Cai, Huibiao Lin, Shuxiang Xie, Erik Goodman
In this paper, we design a set of multi-objective constrained optimization problems (MCOPs) and propose a new repair operator to address them.