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Review on Inertia Weight Strategies for Particle Swarm Optimization

2017
In the category of swarm intelligence based algorithms, Particle Swarm Optimization (PSO) is an effective population-based metaheuristic used to solve complex optimization problems. In PSO, global optima is searched with the help of individuals. For the efficient search process, individuals have to explore whole search space as well as have to exploit ...
Ankush Rathore, Harish Sharma
openaire   +1 more source

Assessment of an evolutionary particle swarm optimizer with inertia weight

2011 IEEE Congress of Evolutionary Computation (CEC), 2011
This paper proposes a newly evolutionary particle swarm optimizer with inertia weight (EPSOIW) for obtaining the PSOIW with high performance. Due to the use of meta-optimization, it can systematically estimate appropriate values of parameters in the PSOIW corresponding to a given optimization problem without prior knowledge.
openaire   +1 more source

Time and Space, Weight and Inertia

American Journal of Physics, 1967
A. D. Fokker, Arthur Komar
openaire   +2 more sources

Inertia Weight Adaption in Particle Swarm Optimization Algorithm

2011
In Particle Swarm Optimization (PSO), setting the inertia weight w is one of the most important topics. The inertia weight was introduced into PSO to balance between its global and local search abilities. In this paper, first, we propose a method to adaptively adjust the inertia weight based on particle's velocity information.
Zheng Zhou, Yuhui Shi
openaire   +1 more source

Performance Evaluation of WMNs by WMN-PSOHC System Considering Random Inertia Weight and Linearly Decreasing Inertia Weight Replacement Methods

2019
Wireless Mesh Networks (WMNs) have many advantages such as low cost and increased high-speed wireless Internet connectivity, therefore WMNs are becoming an important networking infrastructure. In our previous work, we implemented a Particle Swarm Optimization (PSO) based simulation system for node placement in WMNs, called WMN-PSO. Also, we implemented
Shinji Sakamoto, Seiji Ohara, Leonard Barolli, Shusuke Okamoto   +3 more
openaire   +1 more source

Inertia Weight Strategies in GbLN-PSO for Optimum Solution

2023 IEEE 8th International Conference On Software Engineering and Computer Systems (ICSECS), 2023
Nurul Izzatie Husna Fauzi, Zalili Binti Musa   +1 more
openaire   +1 more source

Dynamic Inertia Weight in Particle Swarm Optimization

2017
This paper proposes a particle swarm optimization method with a novel strategy for inertia weight. Instead of a commonly used linear inertia weight, a nonlinear, dynamic changing inertia weight is applied. The new presented weight is a function of the worst and the best fitness of individuals of a population.
openaire   +1 more source

The determination of the most suitable inertia weight strategy for particle swarm optimization via the minimax mixed-integer linear programming model

Engineering Computations, 2021
Volkan Soner Özsoy
exaly  

An adaptive inertia weight teaching-learning-based optimization algorithm and its applications

Applied Mathematical Modelling, 2020
Pradeep Singh, Manu Vardhan, Alok Shukla   +2 more
exaly  

A novel particle swarm optimization algorithm with adaptive inertia weight

Applied Soft Computing Journal, 2011
Mohammad Mehdi Ebadzadeh, Reza Safabakhsh, Ahmad Nickabadi   +2 more
exaly