A survey of swarm intelligence for dynamic optimization: Algorithms and applications
Swarm intelligence (SI) algorithms, including ant colony optimization, particle swarm
optimization, bee-inspired algorithms, bacterial foraging optimization, firefly algorithms, fish …
optimization, bee-inspired algorithms, bacterial foraging optimization, firefly algorithms, fish …
[HTML][HTML] Particle swarm optimisation for dynamic optimisation problems: a review
A Rezaee Jordehi - Neural Computing and Applications, 2014 - Springer
Some real-world optimisation problems are dynamic; that is, their objective function and/or
constraints vary over time. Solving such problems is very challenging. Particle swarm …
constraints vary over time. Solving such problems is very challenging. Particle swarm …
A survey of evolutionary continuous dynamic optimization over two decades—Part B
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 …
optimization (EDO) for single-objective unconstrained continuous problems over the last two …
A survey of evolutionary continuous dynamic optimization over two decades—Part A
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 …
with such problems where the search space changes over time. In this two-part article, we …
A general framework of multipopulation methods with clustering in undetectable dynamic environments
To solve dynamic optimization problems, multiple population methods are used to enhance
the population diversity for an algorithm with the aim of maintaining multiple populations in …
the population diversity for an algorithm with the aim of maintaining multiple populations in …
Scaling up dynamic optimization problems: A divide-and-conquer approach
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 …
large-scale dynamic optimization problems are not well studied in the literature. This paper …
A novel multi-swarm algorithm for optimization in dynamic environments based on particle swarm optimization
Optimization in dynamic environment is considered among prominent optimization
problems. There are particular challenges for optimization in dynamic environments, so that …
problems. There are particular challenges for optimization in dynamic environments, so that …
A note on the exclusion operator in multi-swarm PSO algorithms for dynamic environments
J Kazemi Kordestani, MR Meybodi… - Connection …, 2020 - Taylor & Francis
The exclusion operator is a key component in separating the search territory of each
population in multi-population optimisation algorithms for unconstraint continues dynamic …
population in multi-population optimisation algorithms for unconstraint continues dynamic …
Quantum firefly swarms for multimodal dynamic optimization problems
FB Ozsoydan, A Baykasoğlu - Expert Systems with Applications, 2019 - Elsevier
Optimization problems have attracted attention of researchers for decades. Commonly,
problem related data and problem domain are assumed to be exactly known beforehand …
problem related data and problem domain are assumed to be exactly known beforehand …
An adaptive multipopulation framework for locating and tracking multiple optima
Multipopulation methods are effective in solving dynamic optimization problems. However,
to efficiently track multiple optima, algorithm designers need to address a key issue: how to …
to efficiently track multiple optima, algorithm designers need to address a key issue: how to …