Size/Layout Optimization of Truss Structures Using Vibrating Particles System Meta-heuristic Algorithm and its Improved Version

Vibrating Particles System (VPS) optimization is a newly made meta-heuristic algorithm to optimize problems by inspiration of the free vibration of viscous-damped systems with single degree of freedom. The agents are modeled as particles which systematically proceed toward their equilibrium conditio...

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Vydané v:Periodica polytechnica. Civil engineering. Bauingenieurwesen Ročník 66; číslo 1; s. 1
Hlavní autori: Kaveh, Ali, Khosravian, Masoud
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Budapest Periodica Polytechnica, Budapest University of Technology and Economics 01.01.2022
Predmet:
Algorithms
Equilibrium conditions
Free vibration
Heuristic methods
Optimization
Parameters
Performance evaluation
Problem solving
Vibration
ISSN:0553-6626, 1587-3773
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Shrnutí:Vibrating Particles System (VPS) optimization is a newly made meta-heuristic algorithm to optimize problems by inspiration of the free vibration of viscous-damped systems with single degree of freedom. The agents are modeled as particles which systematically proceed toward their equilibrium conditions that are reached by the existing population and historically best position. To enhance the performance of the VPS algorithm, Enhanced Vibrating Particles System (EVPS) applies a new process for updating agent’s positions. This paper tries to improve the EVPS algorithm with the aim of reduction in the regulatory parameters’ effect on the algorithm's performance by reducing the regulatory parameters. To evaluate the performance of the proposed method, it is applied to four optimization problems of truss structures including mixed of discrete and continuous design search spaces with displacement, stress and buckling constraints. As a result, the proposed algorithm is a suitable method and more research can be done on it.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:0553-6626
1587-3773
DOI:10.3311/PPci.18670