Hybridizing salp swarm algorithm with particle swarm optimization algorithm for recent optimization functions
The salp swarm algorithm (SSA) has shown its fast search speed in several challenging
problems. Research shows that not every nature-inspired approach is suitable for all …
problems. Research shows that not every nature-inspired approach is suitable for all …
Soft computing in engineering design–A review
KM Saridakis, AJ Dentsoras - Advanced Engineering Informatics, 2008 - Elsevier
The present paper surveys the application of soft computing (SC) techniques in engineering
design. Within this context, fuzzy logic (FL), genetic algorithms (GA) and artificial neural …
design. Within this context, fuzzy logic (FL), genetic algorithms (GA) and artificial neural …
An enhanced Archimedes optimization algorithm based on Local esca** operator and Orthogonal learning for PEM fuel cell parameter identification
Meta-heuristic optimization algorithms aim to tackle real world problems through maximizing
some specific criteria such as performance, profit, and quality or minimizing others such as …
some specific criteria such as performance, profit, and quality or minimizing others such as …
A modified Marine Predator Algorithm based on opposition based learning for tracking the global MPP of shaded PV system
Under partial shading condition, the power-voltage curve of the photovoltaic (PV) system
contains several maximum power points (MPPs). Among these points, there is only single …
contains several maximum power points (MPPs). Among these points, there is only single …
An efficient orthogonal opposition-based learning slime mould algorithm for maximum power point tracking
The slime mould algorithm (SMA) is a recent physics-based optimization approach. The
main inspiration of the SMA is motivated by the natural oscillating state of the slime mould …
main inspiration of the SMA is motivated by the natural oscillating state of the slime mould …
Multi-objective design optimisation of rolling bearings using genetic algorithms
The design of rolling bearings has to satisfy various constraints, eg the geometrical,
kinematics and the strength, while delivering excellent performance, long life and high …
kinematics and the strength, while delivering excellent performance, long life and high …
HSSAHHO: a novel hybrid Salp swarm-Harris hawks optimization algorithm for complex engineering problems
With Metaheuristic algorithms hybridization is used typically to improve the performances of
original algorithm, so it became a recent trend of research is to hybridize two and several …
original algorithm, so it became a recent trend of research is to hybridize two and several …
Optimization of module, shaft diameter and rolling bearing for spur gear through genetic algorithm
In this study, dimensioning optimization of the motion and force transmitting components of a
gearbox through genetic algorithm (GA) was performed. Gearbox shaft, gear and rolling …
gearbox through genetic algorithm (GA) was performed. Gearbox shaft, gear and rolling …
Optimum design of rolling element bearings using genetic algorithms
A constraint non-linear optimization procedure based on genetic algorithms has been
developed for designing rolling element bearings. Based on maximum fatigue life as …
developed for designing rolling element bearings. Based on maximum fatigue life as …
Multi-strategy Gaussian Harris hawks optimization for fatigue life of tapered roller bearings
Bearing is one of the most fundamental components of rotary machinery, and its fatigue life
is a crucial factor in designing. The design optimization of tapered roller bearing (TRB) is a …
is a crucial factor in designing. The design optimization of tapered roller bearing (TRB) is a …