Sorting

Techniques for Accelerating Multi-Objective Evolutionary Algorithms in PlatEMO
It has been widely recognized that evolutionary computation is one of the most effective techniques for solving complex optimization …
Ye Tian, Ran Cheng, Xingyi Zhang, Yaochu Jin
Cite DOI
A Decision Variable Clustering-Based Evolutionary Algorithm for Large-Scale Many-Objective Optimization
The current literature of evolutionary many-objective optimization is merely focused on the scalability to the number of objectives, …
Xingyi Zhang, Ye Tian, Ran Cheng, Yaochu Jin
Cite DOI
Evolutionary Many-Objective Optimization of Hybrid Electric Vehicle Control: From General Optimization to Preference Articulation
Many real-world optimization problems have more than three objectives, which has triggered increasing research interest in developing …
Ran Cheng, Tobias Rodemann, Michael Fischer, Markus Olhofer, Yaochu Jin
Cite DOI
PlatEMO: A MATLAB Platform for Evolutionary Multi-Objective Optimization [Educational Forum]
Over the last three decades, a large number of evolutionary algorithms have been developed for solving multi-objective optimization …
Ye Tian, Ran Cheng, Xingyi Zhang, Yaochu Jin
Cite DOI
Empirical Analysis of a Tree-based Efficient Non-dominated Sorting Approach for Many-objective Optimization
Non-dominated sorting has been widely adopted in evolutionary multi-objective optimization. Many approaches to non-dominated sorting …
Xingyi Zhang, Ye Tian, Ran Cheng, Yaochu Jin
Cite DOI
An Efficient Approach to Nondominated Sorting for Evolutionary Multiobjective Optimization
Evolutionary algorithms have been shown to be powerful for solving multiobjective optimization problems, in which nondominated sorting …
Xingyi Zhang, Ye Tian, Ran Cheng, Yaochu Jin
Cite DOI