Multi-objective evolutionary algorithms (MOEAs) have shown promising performance in
solving various optimization problems, but their performance may deteriorate drastically …

Large-scale global optimization (LSGO) problems have widely appeared in various real-
world applications. However, their inherent complexity, coupled with the curse of …

The interests in evolutionary constrained multiobjective optimization are rapidly increasing
during the past two decades. However, most related studies are limited to small-scale …

Most existing evolutionary search strategies are not so efficient when directly handling the
decision space of large-scale multiobjective optimization problems (LMOPs). To enhance …

The generation and updating of solutions, eg, crossover and mutation, of many existing
evolutionary algorithms directly operate on decision variables. The operators are very time …

In large-scale multiobjective optimization, too many decision variables hinder the
convergence search of evolutionary algorithms. Reducing the search range of the decision …

This article is the second part of a two-part survey series on large-scale global optimization.
The first part covered two major algorithmic approaches to large-scale optimization, namely …

Evolutionary transfer optimization (ETO) has been becoming a hot research topic in the field
of evolutionary computation, which is based on the fact that knowledge learning and transfer …

In surrogate-assisted multi-/many-objective evolutionary optimization, each solution
normally has an approximated value on each objective, resulting in increased difficulties in …

Air traffic flow management (ATFM) is the key driver of efficient aviation. It aims at balancing
traffic demand against airspace capacity by scheduling aircraft, which is critical for air …