This article presents the second Part of a two-Part survey that reviews evolutionary dynamic
optimization (EDO) for single-objective unconstrained continuous problems over the last two …

Many real-world optimization problems are dynamic. The field of dynamic optimization deals
with such problems where the search space changes over time. In this two-part article, we …

As science and technology advance, more engineering-type problems emerge. Technology
development has likewise led to an increase in the complexity of optimization problems, and …

The exclusion operator is a key component in separating the search territory of each
population in multi-population optimisation algorithms for unconstraint continues dynamic …

Dynamic multimodal optimization problems (DMMOPs) have to search multiple global
optimal solutions with the objectives and constraints dynamically changing over time. In …

Many vision-based systems suffer from poor levels of contrast and brightness, mainly
because of inadequate and improper illumination during the image acquisition process. As a …

The solution spaces of many real-world optimization problems change over time. Such
problems are called dynamic optimization problems (DOPs), which pose unique challenges …

Optimization problems have attracted attention of researchers for decades. Commonly,
problem related data and problem domain are assumed to be exactly known beforehand …

Although cooperative coevolutionary algorithms are developed for large-scale dynamic
optimization via subspace decomposition, they still face difficulties in reacting to …

In dynamic optimization problems, although the problem environments keep changing, a
new environment is usually related to its previous environments. Based on the relevance …