Measuring the population diversity in metaheuristics has become a common practice for adaptive approaches, aiming mainly to address the issue of premature convergence. Understanding the processes leading to a diversity loss in a metaheuristic algorithm is crucial for designing successful adaptive approaches. In this study, we focus on the relation of the neighborhood size and the rate of diversity loss in the Particle Swarm Optimization algorithm with local topology (also known as LPSO). We argue that the neighborhood size is an important input to consider when designing any adaptive approach based on the change of population diversity. We used the extensive benchmark suite of the IEEE CEC 2014 competition for experiments
Abstract Particle Swarm Optimization is an evolutionary optimization algorithm, large...
Particle Swarm Optimisation has two salient components: a dynamical rule governing particle motion a...
Over the last few decades, many population-based swarm and evolutionary algorithms were introduced i...
Measuring the population diversity in metaheuristics has become a common practice for adaptive appro...
Niching is an important technique for multimodal optimization. Most existing niching methods require...
Abstract—Niching is an important technique for multimodal optimization. Most existing niching method...
Abstract: A new particle optimization algorithm with dynamic topology is proposed based on ‘small wo...
Abstract: A new particle optimization algorithm with dynamic topology is proposed based on a small w...
Premature convergence happens in Particle Swarm Optimization (PSO) partially due to improper search ...
In evolutionary algorithm, population diversity is an important factor for solving performance. In t...
This paper is a collection of the three papers [1][2][3] that presented by the author at internation...
In Particle Swarm Optimization (PSO) with local neighbourhood, the social part of change in the par...
The particle swarm algorithm is a computational method to optimize a problem iteratively. As the nei...
Abstract — During the last couple of decades, evolutionary and swarm intelligence algorithms have si...
Fitness landscapes facilitate the analysis of optimisation problems in a detailed, yet intuitive man...
Abstract Particle Swarm Optimization is an evolutionary optimization algorithm, large...
Particle Swarm Optimisation has two salient components: a dynamical rule governing particle motion a...
Over the last few decades, many population-based swarm and evolutionary algorithms were introduced i...
Measuring the population diversity in metaheuristics has become a common practice for adaptive appro...
Niching is an important technique for multimodal optimization. Most existing niching methods require...
Abstract—Niching is an important technique for multimodal optimization. Most existing niching method...
Abstract: A new particle optimization algorithm with dynamic topology is proposed based on ‘small wo...
Abstract: A new particle optimization algorithm with dynamic topology is proposed based on a small w...
Premature convergence happens in Particle Swarm Optimization (PSO) partially due to improper search ...
In evolutionary algorithm, population diversity is an important factor for solving performance. In t...
This paper is a collection of the three papers [1][2][3] that presented by the author at internation...
In Particle Swarm Optimization (PSO) with local neighbourhood, the social part of change in the par...
The particle swarm algorithm is a computational method to optimize a problem iteratively. As the nei...
Abstract — During the last couple of decades, evolutionary and swarm intelligence algorithms have si...
Fitness landscapes facilitate the analysis of optimisation problems in a detailed, yet intuitive man...
Abstract Particle Swarm Optimization is an evolutionary optimization algorithm, large...
Particle Swarm Optimisation has two salient components: a dynamical rule governing particle motion a...
Over the last few decades, many population-based swarm and evolutionary algorithms were introduced i...