Quorum-sensing peptides (QSPs) are the signal molecules that are closely associated with
diverse cellular processes, such as cell–cell communication, and gene expression …

Evolutionary algorithms have been shown to be very successful in solving multi-objective
optimization problems (MOPs). However, their performance often deteriorates when solving …

In this paper, a new Multi-Objective Arithmetic Optimization Algorithm (MOAOA) is proposed
for solving Real-World constrained Multi-objective Optimization Problems (RWMOPs). Such …

The performance of decomposition-based algorithms is sensitive to the Pareto front shapes
since their reference vectors preset in advance are not always adaptable to various problem …

Aims: The study aims to find a way to reduce the dimensionality of the dataset. Background:
Dimensionality reduction is the key issue of the machine learning process. It does not only …

Due to the curse of dimensionality of search space, it is extremely difficult for evolutionary
algorithms to approximate the optimal solutions of large-scale multiobjective optimization …

Feature selection (FS) has received significant attention since the use of a well-selected
subset of features may achieve better classification performance than that of full features in …

This article suggests a multimodal multiobjective evolutionary algorithm with dual clustering
in decision and objective spaces. One clustering is run in decision space to gather nearby …

Exploring the relationships between the properties of steels and their compositions and
manufacturing parameters is extremely crucial and indispensable to understanding the …

Multiobjective evolutionary algorithms based on decomposition (MOEA/D) have attracted
tremendous attention and achieved great success in the fields of optimization and decision …