Multiobjective evolutionary algorithms (MOEAs) have been widely used in real-world
applications. However, most MOEAs based on Pareto-dominance handle many-objective …

Abstract Gene Expression Programming (GEP) is a popular and established evolutionary
algorithm for automatic generation of computer programs. In recent decades, GEP has …

Over the last three decades, a large number of evolutionary algorithms have been
developed for solving multi-objective optimization problems. However, there lacks an upto …

The current literature of evolutionary many-objective optimization is merely focused on the
scalability to the number of objectives, while little work has considered the scalability to the …

Many-objective optimization has posed a great challenge to the classical Pareto dominance-
based multiobjective evolutionary algorithms (MOEAs). In this paper, an evolutionary …

Evolutionary algorithms (EAs) have shown to be promising in solving many-objective
optimization problems (MaOPs), where the performance of these algorithms heavily …

In the past two decades, multi-objective optimization has attracted increasing interests in the
evolutionary computation community, and a variety of multi-objective optimization algorithms …

Balancing convergence and diversity plays a key role in evolutionary multiobjective
optimization (EMO). Most current EMO algorithms perform well on problems with two or three …

The decomposition-based multiobjective evolutionary algorithms (MOEAs) generally make
use of aggregation functions to decompose a multiobjective optimization problem into …

We provide a derivation of the Poisson multi-Bernoulli mixture (PMBM) filter for multitarget
tracking with the standard point target measurements without using probability generating …