Recent years have seen a tremendous growth in Artificial Intelligence (AI)-based
methodological development in a broad range of domains. In this rapidly evolving field …

Evolutionary algorithms (EAs) possess strong problem-solving abilities and have been
applied in a wide range of applications. However, they still suffer from a high computational …

Until recently, the potential to transfer evolved skills across distinct optimization problem
instances (or tasks) was seldom explored in evolutionary computation. The concept of …

PlatEMO is an open-source platform for solving complex optimization problems, which
provides a variety of metaheuristics including evolutionary algorithms, swarm intelligence …

Recent decades have witnessed great advancements in multiobjective evolutionary
algorithms (MOEAs) for multiobjective optimization problems (MOPs). However, these …

Evolutionary multi-task optimization (EMTO) is an optimization algorithm designed to
optimize multiple tasks simultaneously. In real life, different tasks often correlate to each …

Swarm intelligence algorithms, which are developed for solving complex optimization
problems designed by focusing on simulating the social behavior of one species of simple …

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 …

Evolutionary multi-task optimization (EMTO) is a new branch of evolutionary algorithm (EA)
that aims to optimize multiple tasks simultaneously within a same problem and output the …

Cloud platforms scheduling resources based on the demand of the tasks submitted by the
users, is critical to the cloud provider's interest and customer satisfaction. In this paper, we …