51 citations · 75 across the 6 of their papers we have counts for
6 papers · 1 filter
HV-Net: Hypervolume Approximation based on DeepSets
Ke Shang, Weiyu Chen, Weiduo Liao +1
In this letter, we propose HV-Net, a new method for hypervolume approximation in evolutionary multi-objective optimization. The basic idea of HV-Net is to use DeepSets, a deep neur…
Clustering-Based Subset Selection in Evolutionary Multiobjective Optimization
Weiyu Chen, Hisao Ishibuchi, Ke Shang
Subset selection is an important component in evolutionary multiobjective optimization (EMO) algorithms. Clustering, as a classic method to group similar data points together, has…
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…
Fast Greedy Subset Selection from Large Candidate Solution Sets in Evolutionary Multi-objective Optimization
Weiyu Chen, Hisao Ishibuchi, Ke Shang
Subset selection is an interesting and important topic in the field of evolutionary multi-objective optimization (EMO). Especially, in an EMO algorithm with an unbounded external a…
Lazy Greedy Hypervolume Subset Selection from Large Candidate Solution Sets
Weiyu Chen, Hisao Ishibuhci, Ke Shang
Subset selection is a popular topic in recent years and a number of subset selection methods have been proposed. Among those methods, hypervolume subset selection is widely used. G…
Effects of Discretization of Decision and Objective Spaces on the Performance of Evolutionary Multiobjective Optimization Algorithms
Weiyu Chen, Hisao Ishibuchi, Ke Shang
Recently, the discretization of decision and objective spaces has been discussed in the literature. In some studies, it is shown that the decision space discretization improves the…