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 …

There exist many multiobjective optimization problems (MOPs) containing a large number of
decision variables in real-world applications, which are known as large-scale MOPs. Due to …

As a powerful optimization technique, multi-objective particle swarm optimization algorithms
have been widely used in various fields. However, performing well in terms of convergence …

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

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 …

Recently, MOEA/D (multi-objective evolutionary algorithm based on decomposition) has
achieved great success in the field of evolutionary multi-objective optimization and has …

Feature selection is a multi-objective optimization problem since it has two conflicting
objectives: maximizing the classification accuracy and minimizing the number of the …

Recently, it was found that most multiobjective particle swarm optimizers (MOPSOs) perform
poorly when tackling many-objective optimization problems (MaOPs). This is mainly …

Recently, multi-objective particle swarm optimization (MOPSO) has shown the effectiveness
in solving multi-objective optimization problems (MOPs). However, most MOPSO algorithms …

This paper investigates the path planning problem for unmanned surface vehicle (USV),
wherein the goal is to find the shortest, smoothest, most economical and safest path in the …