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 …

Scalability is a crucial aspect of designing efficient algorithms. Despite their prevalence,
large-scale dynamic optimization problems are not well studied in the literature. This paper …

Self-adaptation is a popular parameter control technique in evolutionary computation, which
has been extensively studied in stationary optimisation. In the context of dynamic …

As a task of high importance for recommender systems, we consider the problem of learning
the convex combination of ranking algorithms by online machine learning. First, we propose …

In real world, many optimization problems are dynamic, which means that their model
elements vary with time. These problems have received increasing attention over time …

Dynamic optimization problems typically appear in real-world systems underlying
environmental influence. Solving this kind of problems requires algorithms considering …

Numerical optimization is one of the most active research areas and is widely used in
science, engineering, economics and industry. In numerical black box optimization, the …