Abstract The Artificial Fish Swarm Algorithm (AFSA) is inspired by the ecological behaviors
of fish schooling in nature, viz., the preying, swarming and following behaviors. Owing to a …

Swarm intelligence (SI) algorithms, including ant colony optimization, particle swarm
optimization, bee-inspired algorithms, bacterial foraging optimization, firefly algorithms, fish …

Dynamic changes are an important and inescapable aspect of many real-world optimization
problems. Designing algorithms to find and track desirable solutions while facing challenges …

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 …

Robust optimization over time is a new way to tackle dynamic optimization problems where
the goal is to find solutions that remain acceptable over an extended period of time. The …

The collective behaviour of fish schools, shoals and other swarms in nature has long
inspired researchers to develop solutions for optimization problems. Instinct influences the …

Dynamic optimization problems (DOPs) are problems that change over time. However, most
investigations in this domain are focused on tracking moving optima (TMO) without …

An existing high-speed railway tunnel undercrossed by shield tunnelling is a high-risk
project. Selecting reasonable shield tunnelling parameters is key in controlling the …

Multipopulation methods are highly effective in solving dynamic optimization problems.
Three factors affect this significantly: 1) the exclusion mechanisms to avoid the convergence …