Efficient initialization methods for population-based metaheuristic algorithms: A comparative study
The size, nature, and diversity of the initial population of population-based metaheuristic
algorithms and the number of times the algorithm iterates play a significant role in the …
algorithms and the number of times the algorithm iterates play a significant role in the …
Design of computer experiments: A review
In this article, we present a detailed overview of the literature on the design of computer
experiments. We classify the existing literature broadly into two categories, viz. static and …
experiments. We classify the existing literature broadly into two categories, viz. static and …
A distance-based locally informed particle swarm model for multimodal optimization
Multimodal optimization amounts to finding multiple global and local optima (as opposed to
a single solution) of a function, so that the user can have a better knowledge about different …
a single solution) of a function, so that the user can have a better knowledge about different …
Parameter selection in particle swarm optimisation: a survey
A Rezaee Jordehi, J Jasni - Journal of Experimental & Theoretical …, 2013 - Taylor & Francis
Nowadays, particle swarm optimisation (PSO) is one of the most commonly used
optimisation techniques. However, PSO parameters significantly affect its computational …
optimisation techniques. However, PSO parameters significantly affect its computational …
Comparative analysis of low discrepancy sequence-based initialization approaches using population-based algorithms for solving the global optimization problems
Metaheuristic algorithms have been widely used to solve diverse kinds of optimization
problems. For an optimization problem, population initialization plays a significant role in …
problems. For an optimization problem, population initialization plays a significant role in …
A review of population initialization techniques for evolutionary algorithms
Although various population initialization techniques have been employed in evolutionary
algorithms (EAs), there lacks a comprehensive survey on this research topic. To fill this gap …
algorithms (EAs), there lacks a comprehensive survey on this research topic. To fill this gap …
Real-parameter evolutionary multimodal optimization—A survey of the state-of-the-art
Multimodal optimization amounts to finding multiple global and local optima (as opposed to
a single solution) of a function, so that the user can have a better knowledge about different …
a single solution) of a function, so that the user can have a better knowledge about different …
Initialisation approaches for population-based metaheuristic algorithms: a comprehensive review
JO Agushaka, AE Ezugwu - Applied Sciences, 2022 - mdpi.com
A situation where the set of initial solutions lies near the position of the true optimality (most
favourable or desirable solution) by chance can increase the probability of finding the true …
favourable or desirable solution) by chance can increase the probability of finding the true …
An overview of particle swarm optimization variants
Particle swarm optimization (PSO) is a stochastic algorithm used for the optimization
problems proposed by Kennedy [1] in 1995. It is a very good technique for the optimization …
problems proposed by Kennedy [1] in 1995. It is a very good technique for the optimization …
A new population initialization of metaheuristic algorithms based on hybrid fuzzy rough set for high-dimensional gene data feature selection
X Guo, J Hu, H Yu, M Wang, B Yang - Computers in Biology and Medicine, 2023 - Elsevier
In the realm of modern medicine and biology, vast amounts of genetic data with high
complexity are available. However, dealing with such high-dimensional data poses …
complexity are available. However, dealing with such high-dimensional data poses …