Projekter pr. år
Abstrakt
At present, optimization algorithms are used extensively. One particular type of such algorithms includes randombased heuristic population optimization algorithms, which may be created by modeling scientific phenomena, like, for example, physical processes. The present article proposes a novel optimization algorithm based on Hooke's law, called the spring search algorithm (SSA), which aims to solve singleobjective constrained optimization problems. In the SSA, search agents are weights joined through springs, which, as Hooke's law states, possess a force that corresponds to its length. The mathematics behind the algorithm are presented in the text. In order to test its functionality, it is executed on 38 established benchmark test functions and weighed against eight other optimization algorithms: a genetic algorithm (GA), a gravitational search algorithm (GSA), a grasshopper optimization algorithm (GOA), particle swarm optimization (PSO), teachinglearningbased optimization (TLBO), a grey wolf optimizer (GWO), a spotted hyena optimizer (SHO), as well as an emperor penguin optimizer (EPO). To test the SSA's usability, it is employed on five engineering optimization problems. The SSA delivered better fitting results than the other algorithms in unimodal objective function, multimodal objective functions, CEC 2015, in addition to the optimization problems in engineering.
Originalsprog  Engelsk 

Artikelnummer  6173 
Tidsskrift  Applied Sciences (Switzerland) 
Vol/bind  10 
Udgave nummer  18 
ISSN  20763417 
DOI  
Status  Udgivet  sep. 2020 
Fingeraftryk Dyk ned i forskningsemnerne om 'A spring search algorithm applied to engineering optimization problems'. Sammen danner de et unikt fingeraftryk.
Projekter
 1 Igangværende

CROM: Center for Research on Microgrids
Guerrero, J. M., Vasquez, J. C., Tinajero, G. D. A., Akhavan, A. & Guldbæk, B. K.
01/08/2019 → 31/07/2025
Projekter: Projekt › Forskning