22 citations · 41 across the 4 of their papers we have counts for
4 papers
Learning Pareto Set for Multi-Objective Continuous Robot Control
Tianye Shu, Ke Shang, Cheng Gong +2
For a control problem with multiple conflicting objectives, there exists a set of Pareto-optimal policies called the Pareto set instead of a single optimal policy. When a multi-obj…
Effects of Archive Size on Computation Time and Solution Quality for Multi-Objective Optimization
Tianye Shu, Ke Shang, Hisao Ishibuchi +1
An unbounded external archive has been used to store all nondominated solutions found by an evolutionary multi-objective optimization algorithm in some studies. It has been shown t…
Benchmarking Subset Selection from Large Candidate Solution Sets in Evolutionary Multi-objective Optimization
Ke Shang, Tianye Shu, Hisao Ishibuchi +2
In the evolutionary multi-objective optimization (EMO) field, the standard practice is to present the final population of an EMO algorithm as the output. However, it has been shown…
Hypervolume-Optimal -Distributions on Line/Plane-based Pareto Fronts in Three Dimensions
Ke Shang, Hisao Ishibuchi, Weiyu Chen +2
Hypervolume is widely used in the evolutionary multi-objective optimization (EMO) field to evaluate the quality of a solution set. For a solution set with solutions on a Pareto…