Multi-swarm optimization
View article
A novel swarm intelligence optimization approach: sparrow search algorithm Open
In this paper, a novel swarm optimization approach, namely sparrow search algorithm (SSA), is proposed inspired by the group wisdom, foraging and anti-predation behaviours of sparrows. Experiments on 19 benchmark functions are conducted to…
View article
Particle Swarm Optimization: A Comprehensive Survey Open
Particle swarm optimization (PSO) is one of the most well-regarded swarm-based algorithms in the literature. Although the original PSO has shown good optimization performance, it still severely suffers from premature convergence. As a resu…
View article
A Review on Representative Swarm Intelligence Algorithms for Solving Optimization Problems: Applications and Trends Open
Swarm intelligence algorithms are a subset of the artificial intelligence (AI) field, which is increasing popularity in resolving different optimization problems and has been widely utilized in various applications. In the past decades, nu…
View article
Artificial Neural Networks Based Optimization Techniques: A Review Open
In the last few years, intensive research has been done to enhance artificial intelligence (AI) using optimization techniques. In this paper, we present an extensive review of artificial neural networks (ANNs) based optimization algorithm …
View article
Data-Driven Evolutionary Optimization: An Overview and Case Studies Open
Most evolutionary optimization algorithms assume that the evaluation of the objective and constraint functions is straightforward. In solving many real-world optimization problems, however, such objective functions may not exist, instead c…
View article
An Overview of Variants and Advancements of PSO Algorithm Open
Particle swarm optimization (PSO) is one of the most famous swarm-based optimization techniques inspired by nature. Due to its properties of flexibility and easy implementation, there is an enormous increase in the popularity of this natur…
View article
Northern Goshawk Optimization: A New Swarm-Based Algorithm for Solving Optimization Problems Open
Optimization algorithms are one of the effective stochastic methods in solving optimization problems. In this paper, a new swarm-based algorithm called Northern Goshawk Optimization (NGO) algorithm is presented that simulates the behavior …
View article
Particle Swarm Optimization: A Survey of Historical and Recent Developments with Hybridization Perspectives Open
Particle Swarm Optimization (PSO) is a metaheuristic global optimization paradigm that has gained prominence in the last two decades due to its ease of application in unsupervised, complex multidimensional problems that cannot be solved us…
View article
A Novel Sigmoid-Function-Based Adaptive Weighted Particle Swarm Optimizer Open
In this paper, a novel particle swarm optimization (PSO) algorithm is put forward where a sigmoid-function-based weighting strategy is developed to adaptively adjust the acceleration coefficients. The newly proposed adaptive weighting stra…
View article
Population size in Particle Swarm Optimization Open
Particle Swarm Optimization (PSO) is among the most universally applied population-based metaheuristic optimization algorithms. PSO has been successfully used in various scientific fields, ranging from humanities, engineering, chemistry, m…
View article
Social group optimization (SGO): a new population evolutionary optimization technique Open
Social group optimization (SGO), a population-based optimization technique is proposed in this paper. It is inspired from the concept of social behavior of human toward solving a complex problem. The concept and the mathematical formulatio…
View article
A Dynamic Neighborhood-Based Switching Particle Swarm Optimization Algorithm Open
In this article, a dynamic-neighborhood-based switching PSO (DNSPSO) algorithm is proposed, where a new velocity updating mechanism is designed to adjust the personal best position and the global best position according to a distance-based…
View article
Coevolutionary Particle Swarm Optimization With Bottleneck Objective Learning Strategy for Many-Objective Optimization Open
The application of multiobjective evolutionary algorithms to many-objective optimization problems often faces challenges in terms of diversity and convergence. On the one hand, with a limited population size, it is difficult for an algorit…
View article
Co-evolutionary particle swarm optimization algorithm for two-sided robotic assembly line balancing problem Open
Industries utilize two-sided assembly lines for producing large-sized volume products such as cars and trucks. By employing robots, industries achieve a high level of automation in the assembly process. Robots help to replace human labor a…
View article
Subtraction-Average-Based Optimizer: A New Swarm-Inspired Metaheuristic Algorithm for Solving Optimization Problems Open
This paper presents a new evolutionary-based approach called a Subtraction-Average-Based Optimizer (SABO) for solving optimization problems. The fundamental inspiration of the proposed SABO is to use the subtraction average of searcher age…
View article
Particle swarm optimization based on dimensional learning strategy Open
In traditional particle swarm optimization (PSO) algorithm, each particle updates its velocity and position with a learning mechanism based on its personal best experience and the population best experience. The learning mechanism in tradi…
View article
Adaptive Granularity Learning Distributed Particle Swarm Optimization for Large-Scale Optimization Open
Large-scale optimization has become a significant and challenging research topic in the evolutionary computation (EC) community. Although many improved EC algorithms have been proposed for large-scale optimization, the slow convergence in …
View article
Sea Lion Optimization Algorithm Open
This paper suggests a new nature inspired metaheuristic optimization algorithm which is called Sea Lion Optimization (SLnO) algorithm. The SLnO algorithm imitates the hunting behavior of sea lions in nature. Moreover, it is inspired by sea…
View article
A New Quadratic Binary Harris Hawk Optimization for Feature Selection Open
Harris hawk optimization (HHO) is one of the recently proposed metaheuristic algorithms that has proven to be work more effectively in several challenging optimization tasks. However, the original HHO is developed to solve the continuous o…
View article
A Particle Swarm Optimization-Based Flexible Convolutional Autoencoder for Image Classification Open
Convolutional autoencoders (CAEs) have shown their remarkable performance in stacking to deep convolutional neural networks (CNNs) for classifying image data during the past several years. However, they are unable to construct the state-of…
View article
A multi-swarm particle swarm optimization algorithm based on dynamical topology and purposeful detecting Open
This paper proposes a multi-swarm particle swarm optimization (MSPSO) that consists of three novel strategies to balance the exploration and exploitation abilities. The new proposed MSPSO in this work is based on multiple swarms framework …
View article
A Review on Constraint Handling Techniques for Population-based Algorithms: from single-objective to multi-objective optimization Open
Most real-world problems involve some type of optimization problems that are often constrained. Numerous researchers have investigated several techniques to deal with constrained single-objective and multi-objective evolutionary optimizati…
View article
Dynamic differential annealed optimization: New metaheuristic optimization algorithm for engineering applications Open
This work proposes a novel optimization algorithm which can be used to solve a wide range of mathematical optimization problems where the global minimum or maximum is required. The new algorithm is based on random search and classical simu…
View article
Cat Swarm Optimization Algorithm: A Survey and Performance Evaluation Open
This paper presents an in-depth survey and performance evaluation of cat swarm optimization (CSO) algorithm. CSO is a robust and powerful metaheuristic swarm-based optimization approach that has received very positive feedback since its em…
View article
A hybrid particle swarm optimization and genetic algorithm with population partitioning for large scale optimization problems Open
In this paper, a new hybrid particle swarm optimization and genetic algorithm is proposed to minimize a simplified model of the energy function of the molecule. The proposed algorithm is called Hybrid Particle Swarm Optimization and Geneti…
View article
Performance of Elephant Herding Optimization and Tree Growth Algorithm Adapted for Node Localization in Wireless Sensor Networks Open
Wireless sensor networks, as an emerging paradigm of networking and computing, have applications in diverse fields such as medicine, military, environmental control, climate forecasting, surveillance, etc. For successfully tackling the nod…
View article
Solving Constrained Trajectory Planning Problems Using Biased Particle Swarm Optimization Open
Constrained trajectory optimization has been a critical component in the development of advanced guidance and control systems. An improperly planned reference trajectory can be a main cause of poor online control performance. Due to the ex…
View article
A comprehensive survey: Applications of multi-objective particle swarm optimization (mopso) algorithm Open
Numerous problems encountered in real life cannot be actually formulated as a single objective problem; hence the requirement of Multi-Objective Optimization (MOO) had arisen several years ago. Due to the complexities in such type of probl…
View article
Teamwork Optimization Algorithm: A New Optimization Approach for Function Minimization/Maximization Open
Population-based optimization algorithms are one of the most widely used and popular methods in solving optimization problems. In this paper, a new population-based optimization algorithm called the Teamwork Optimization Algorithm (TOA) is…
View article
A New Optimization Algorithm Based on Search and Rescue Operations Open
In this paper, a new optimization algorithm called the search and rescue optimization algorithm (SAR) is proposed for solving single‐objective continuous optimization problems. SAR is inspired by the explorations carried out by humans duri…