Design optimization of a car side safety system by particle swarm optimization and grey wolf optimizer

2021 ◽  
pp. 15-24
Author(s):  
Ikram Hamadache ◽  
Mohamed Arezki Mellal
Keyword(s):  
Particle Swarm Optimization ◽  
Design Optimization ◽  
Particle Swarm ◽  
Safety System ◽  
Grey Wolf Optimizer ◽  
Grey Wolf ◽  
Swarm Optimization

scholarly journals Hybrid Algorithm of Particle Swarm Optimization and Grey Wolf Optimizer for Improving Convergence Performance

2017 ◽  
Vol 2017 ◽  
pp. 1-15 ◽  
Author(s):  
Narinder Singh ◽  
S. B. Singh
Keyword(s):  
Particle Swarm Optimization ◽  
Particle Swarm ◽  
Main Idea ◽  
Grey Wolf Optimizer ◽  
Solution Stability ◽  
Grey Wolf ◽  
Solution Quality ◽  
Swarm Optimization ◽  
Fixed Dimension ◽  
Nature Inspired Algorithm

A newly hybrid nature inspired algorithm called HPSOGWO is presented with the combination of Particle Swarm Optimization (PSO) and Grey Wolf Optimizer (GWO). The main idea is to improve the ability of exploitation in Particle Swarm Optimization with the ability of exploration in Grey Wolf Optimizer to produce both variants’ strength. Some unimodal, multimodal, and fixed-dimension multimodal test functions are used to check the solution quality and performance of HPSOGWO variant. The numerical and statistical solutions show that the hybrid variant outperforms significantly the PSO and GWO variants in terms of solution quality, solution stability, convergence speed, and ability to find the global optimum.

scholarly journals Solving Economic Load Dispatch Problem using Grey Wolf Optimizer Method

2019 ◽  
Vol 8 (4) ◽  
pp. 684-688
Keyword(s):  
Particle Swarm Optimization ◽  
Particle Swarm ◽  
Grey Wolf Optimizer ◽  
Economic Load Dispatch ◽  
Grey Wolf ◽  
Fuel Cost ◽  
Swarm Optimization ◽  
Load Demand ◽  
Alpha Beta ◽  
Critical Phases

The aim of economic load dispatch (ELD) is to accomplish the load demand with less fuel cost by the generators. This research shows a new grey wolf-inspired algorithm called the Grey Wolf Optimizer (GWO) to achieve ELD. The GWO algorithm follows mainly the grey wolves hierarchy and hunting scheme. The controlling hierarchy is driven by four wolves, namely alpha, beta, delta, and omega. Three critical phases of hunting are implemented, looking for a target, surrounding a target, and attacking a target. Now, on 20 generating units, the algorithm is used and is equated with Particle Swarm Optimization (PSO). The findings show that, compared to PSO, the GWO algorithm is set to yield economic results.

scholarly journals Particle Swarm Optimization, Genetic Algorithm and Grey Wolf Optimizer Algorithms Performance Comparative for a DC-DC Boost Converter PID Controller

2021 ◽  
Vol 6 (1) ◽  
pp. 619-625
Author(s):  
Jesus Aguila-Leon ◽  
Cristian Chiñas-Palacios ◽  
Carlos Vargas-Salgado ◽  
Elias Hurtado-Perez ◽  
Edith Xio Mara Garcia
Keyword(s):  
Genetic Algorithm ◽  
Particle Swarm Optimization ◽  
Pid Controller ◽  
Particle Swarm ◽  
Boost Converter ◽  
Grey Wolf Optimizer ◽  
Grey Wolf ◽  
Swarm Optimization
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