Hypervolume (HV)-based evolutionary algorithms have been widely used to handle many-
objective optimization problems. In such algorithms, HV-based environmental selection …

In evolutionary multi-objective optimization (EMO), the pair-potential energy functions (PPFs)
have been used to construct diversity-preserving mechanisms to improve Pareto front …

Most multiobjective optimization algorithms maintain an archive explicitly or implicitly during
their search. Such an archive can be solely used to store high-quality solutions presented to …

Subset selection, which selects a subset of solutions according to certain criterion/indicator,
is a topic closely related to evolutionary multiobjective optimization (EMO). The critical …

Hypervolume subset selection (HSS) has received considerable attention in the field of
evolutionary multiobjective optimization (EMO). It aims to select a representative subset from …

Hypervolume subset selection (HSS) has received significant attention since it has a strong
connection with evolutionary multi-objective optimization (EMO), such as environment …

Subset selection, a fundamental problem in various domains, is to choose a subset of
elements from a large candidate set under a given objective or multiple objectives. Pareto …

Multi-objective optimization problems (MOPs) aim to obtain a set of Pareto-optimal solutions,
and as the number of objectives increases, the quantity of these optimal solutions grows …

Evolutionary multi-objective optimization (EMO) is a highly active research field that has
attracted many researchers and practitioners over the past three decades. Surprisingly, until …

Recently, an R2-based hypervolume contribution approximation (ie, R 2 HVC indicator) has
been proposed and applied to evolutionary multi-objective algorithms and subset selection …