Artificial ecosystem-based optimization: a novel nature-inspired meta-heuristic algorithm
W Zhao, L Wang, Z Zhang - Neural Computing and Applications, 2020 - Springer
A novel nature-inspired meta-heuristic optimization algorithm, named artificial ecosystem-
based optimization (AEO), is presented in this paper. AEO is a population-based optimizer …
based optimization (AEO), is presented in this paper. AEO is a population-based optimizer …
Geyser inspired algorithm: a new geological-inspired meta-heuristic for real-parameter and constrained engineering optimization
Over the past years, many efforts have been accomplished to achieve fast and accurate
meta-heuristic algorithms to optimize a variety of real-world problems. This study presents a …
meta-heuristic algorithms to optimize a variety of real-world problems. This study presents a …
Nature inspired optimization algorithms or simply variations of metaheuristics?
A Tzanetos, G Dounias - Artificial Intelligence Review, 2021 - Springer
In the last decade, we observe an increasing number of nature-inspired optimization
algorithms, with authors often claiming their novelty and their capabilities of acting as …
algorithms, with authors often claiming their novelty and their capabilities of acting as …
Nature inspired optimization algorithms: a comprehensive overview
Nature performs complex tasks in a simple yet efficient way. Natural processes may seem
straightforward from outside but are composed of several inherently complicated sub …
straightforward from outside but are composed of several inherently complicated sub …
Group search optimizer: a nature-inspired meta-heuristic optimization algorithm with its results, variants, and applications
L Abualigah - Neural Computing and Applications, 2021 - Springer
In this paper, to keep the researchers interested in nature-inspired algorithms and
optimization problems, a comprehensive survey of the group search optimizer (GSO) …
optimization problems, a comprehensive survey of the group search optimizer (GSO) …
A systematic review of the emerging metaheuristic algorithms on solving complex optimization problems
The scientific field of optimization has witnessed an increasing trend in the development of
metaheuristic algorithms within the current decade. The vast majority of the proposed …
metaheuristic algorithms within the current decade. The vast majority of the proposed …
A brief review of nature-inspired algorithms for optimization
Swarm intelligence and bio-inspired algorithms form a hot topic in the developments of new
algorithms inspired by nature. These nature-inspired metaheuristic algorithms can be based …
algorithms inspired by nature. These nature-inspired metaheuristic algorithms can be based …
Atom search optimization and its application to solve a hydrogeologic parameter estimation problem
W Zhao, L Wang, Z Zhang - Knowledge-Based Systems, 2019 - Elsevier
In recent years, various metaheuristic optimization methods have been proposed in scientific
and engineering fields. In this study, a novel physics-inspired metaheuristic optimization …
and engineering fields. In this study, a novel physics-inspired metaheuristic optimization …
A survey of biogeography-based optimization
W Guo, M Chen, L Wang, Y Mao, Q Wu - Neural Computing and …, 2017 - Springer
Optimization is a classical issue and in many areas that are bound up with people's daily life.
In current decades, with the development of human civilization and industry society, many …
In current decades, with the development of human civilization and industry society, many …
[PDF][PDF] EvoloPy: An open-source nature-inspired optimization framework in python.
EvoloPy is an open source and cross-platform Python framework that implements a wide
range of classical and recent nature-inspired metaheuristic algorithms. The goal of this …
range of classical and recent nature-inspired metaheuristic algorithms. The goal of this …