An exhaustive review of the metaheuristic algorithms for search and optimization: taxonomy, applications, and open challenges
As the world moves towards industrialization, optimization problems become more
challenging to solve in a reasonable time. More than 500 new metaheuristic algorithms …
challenging to solve in a reasonable time. More than 500 new metaheuristic algorithms …
Salp swarm optimization: a critical review
In the crowded environment of bio-inspired population-based metaheuristics, the Salp
Swarm Optimization (SSO) algorithm recently appeared and immediately gained a lot of …
Swarm Optimization (SSO) algorithm recently appeared and immediately gained a lot of …
Bio-inspired computation: Where we stand and what's next
In recent years, the research community has witnessed an explosion of literature dealing
with the mimicking of behavioral patterns and social phenomena observed in nature towards …
with the mimicking of behavioral patterns and social phenomena observed in nature towards …
Macroscopic resting-state brain dynamics are best described by linear models
It is typically assumed that large networks of neurons exhibit a large repertoire of nonlinear
behaviours. Here we challenge this assumption by leveraging mathematical models derived …
behaviours. Here we challenge this assumption by leveraging mathematical models derived …
Ensemble of differential evolution variants
Differential evolution (DE) is one of the most popular and efficient evolutionary algorithms for
numerical optimization and it has gained much success in a series of academic benchmark …
numerical optimization and it has gained much success in a series of academic benchmark …
[HTML][HTML] A prescription of methodological guidelines for comparing bio-inspired optimization algorithms
Bio-inspired optimization (including Evolutionary Computation and Swarm Intelligence) is a
growing research topic with many competitive bio-inspired algorithms being proposed every …
growing research topic with many competitive bio-inspired algorithms being proposed every …
A carnivorous plant algorithm for solving global optimization problems
In this study, a novel metaheuristic algorithm, namely, carnivorous plant algorithm (CPA),
inspired by how the carnivorous plants adapting to survive in the harsh environment, was …
inspired by how the carnivorous plants adapting to survive in the harsh environment, was …
Q-learning based vegetation evolution for numerical optimization and wireless sensor network coverage optimization
Vegetation evolution (VEGE) is a newly proposed meta-heuristic algorithm (MA) with
excellent exploitation but relatively weak exploration capacity. We thus focus on further …
excellent exploitation but relatively weak exploration capacity. We thus focus on further …
Is the brain macroscopically linear? A system identification of resting state dynamics
A central challenge in the computational modeling of neural dynamics is the trade-off
between accuracy and simplicity. At the level of individual neurons, nonlinear dynamics are …
between accuracy and simplicity. At the level of individual neurons, nonlinear dynamics are …
Infeasibility and structural bias in differential evolution
Structural bias is a recently identified property of optimisation algorithms, causing them to
favour certain regions of the search space over others, independently of the objective …
favour certain regions of the search space over others, independently of the objective …