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

Authors

  • Ali Kaveh
    Affiliation

    School of Civil Engineering, Iran University of Science and Technology, Narmak, Tehran, Postal Code 16846-13114, Iran

  • Masoud Khosravian
    Affiliation

    School of Civil Engineering, Iran University of Science and Technology, Narmak, Tehran, Postal Code 16846-13114, Iran

https://doi.org/10.3311/PPci.18670

Abstract

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.

Keywords:

meta-heuristic algorithms, vibrating particles system algorithm, improved vibrating particles system algorithm, truss optimization, sizing and layout optimization

Citation data from Crossref and Scopus

Published Online

2021-12-21

How to Cite

Kaveh, A., Khosravian, M. “Size/Layout Optimization of Truss Structures Using Vibrating Particles System Meta-heuristic Algorithm and its Improved Version”, Periodica Polytechnica Civil Engineering, 66(1), pp. 1–17, 2022. https://doi.org/10.3311/PPci.18670

Issue

Section

Research Article