Multi-objective optimization of vibrating particle systems applied to engineering system design

Authors

DOI:

https://doi.org/10.5902/2179460X86556

Keywords:

Engineering system design, Vibrating particles system algorithm, Heuristic optimization, Multi-objective optimization

Abstract

The design of systems constitutes one of the most important pillars in engineering, in which it is desired to reduce costs, minimize time and resources, and guarantee the quality, efficiency, and safety of products. In recent decades, numerous population-based algorithms have been employed for this purpose. Among these, we can cite a new heuristic approach, the Vibrating Particles System (VPS) algorithm. This is based on simulating the free vibration of systems with one degree of freedom and viscous damping. The present work aims to extend the VPS to a multi-objective context. The results obtained considering two engineering design problems demonstrate that the proposed methodology was able to obtain good performance in terms of convergence and computational cost.

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Author Biographies

Jéssica Cristiane Andrade, Universidade Federal de Uberlândia

Holds a degree in Mechanical Engineering from the Federal University of Uberlândia (2020). He has experience in the field of Mechanical Engineering.

Fran Sérgio Lobato, Universidade Federal de Uberlândia

Born in Araguari-MG. He obtained the title of Chemical Engineer in 2002, at the Faculty of Chemical Engineering of the Federal University of Uberlândia, where he completed his Master's Thesis, which focused on the Algebraic-Differential Optimal Control Theory, in 2004. In 2008 he completed his PhD Thesis at the Faculty of Mechanical Engineering of the Federal University of Uberlândia, where he worked with the Differential Evolution Algorithm applied to multi-objective problems. He is currently an associate professor at the Federal University of Uberlândia, a permanent professor at the Graduate Program in Modeling and Optimization at the Federal University of Goiás, Catalan Campus and a permanent professor at the Graduate Program in Mechanical Engineering at the Federal University of Uberlândia, Santa Monica Campus. His areas of interest are: i) Algebraic-Differential Optimal Control Theory with Floating Index, with applications in several areas, mainly in biotechnological processes and in medicine for the development of strategies for the treatment of carcinomas; ii) Classical, Heuristic, Structural and Bio-Inspired Optimization Methods; iii) Updating of parameters of evolutionary algorithms using Chaotic Search Models and the Concept of Convergence Rate based on the Concept of Population Homogeneity; iv) Inverse Problems; v) Design of Multi-objective Engineering Systems; vi) Handling Robust Optimization Issues and vii) Handling Optimization Issues with Reliability. 

Gustavo Barbosa Libotte, Universidade do Estado do Rio de Janeiro

Holds a bachelor's degree in Computer Engineering (2010-2014), a master's degree (2014-2015) and a PhD (2016-2020) in Computational Modeling from the State University of Rio de Janeiro. He is currently an adjunct professor at the Department of Computational Modeling at the Polytechnic Institute of the State University of Rio de Janeiro (IPRJ/UERJ) and a permanent professor at the Graduate Program in Computational Modeling at IPRJ/UERJ. Has experience in the area of numerical analysis and stochastic optimization, with emphasis on evolutionary algorithms, parameter estimation and uncertainty analysis.

Gustavo Mendes Platt, Universidade Federal do Rio Grande

He holds a bachelor's degree in Chemical Engineering from the Federal University of Rio de Janeiro (1994), a master's degree in Chemical and Biochemical Process Technology from the Federal University of Rio de Janeiro (1997) and a PhD in Chemical and Biochemical Process Technology from the Federal University of Rio de Janeiro (2001). He is currently an Adjunct Professor at the Federal University of Rio Grande (Santo Antônio da Patrulha campus) and a Permanent Professor of the Graduate Program in Agroindustrial Systems and Processes (PPGSPA/FURG/SAP).  He has experience in the areas of simulation and numerical analysis focused on the problems of separation operations and phase equilibria.

References

Andrade, J. C., Lobato, F. S. (2023). Engineering System Design using the Vibrating Particles System Algorithm. Ciência E Natura, 45(esp. 3), e74073.

Castro, R. E. (2001). Otimização de Estruturas com multi-objetivo via Algoritmos Genéticos de Pareto, Tese de Doutorado, Departamento de Engenharia Civil, COPPE/UFRJ.

Coello, C., Pulido, G., & Lechuga, M. (2004). Handling Multiple Objectives with Particle Swarm Optimization. IEEE Transactions on Evolutionary Computation, 8(3), 256-279.

Deb, K. (2001). Multi-Objective Optimization using Evolutionary Algorithms. Chichester (England): John Wiley & Sons.

Kaveh, A. (2017). Vibrating particles system algorithm. In: Advances in Metaheuristic Algorithms for Optimal Design of Structures. Switzerland: Springer, 511-539.

Kaveh, A., & Ghazaan, M. I. (2017). Vibrating particles system algorithm for truss optimization with multiple natural frequency constraints. Acta Mechanica, Springer, 228(1), 307-322.

Kaveh, A., & Vazirinia, Y. (2017). Tower Cranes and Supply Points Locating Problem using CBO, ECBO, and VPS. International Journal of Optimization in Civil Engineering, 7, 393-411.

Kaveh, A., & Jafarpour, D. (2017). Optimal Design of Reinforced Concrete Cantilever Retaining Walls using CBO, ECBO and VPS Algorithms. Asian Journal of Civil Engineering, 18, 657-671, 2017.

Lobato, F. S. (2008). Otimização multi-objetivo para o projeto de sistemas de engenharia. Tese (Doutorado em Engenharia Mecânica) –

Universidade Federal de Uberlândia, Uberlândia.

Ravindran, A., Ragsdell, K. M., & Reklaitis, G. V. (2009). Engineering Optimization: Methods and Applications, 2 ed., John Wiley & Sons, Hoboken, New Jersey.

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Published

2024-11-04

How to Cite

Andrade, J. C., Lobato, F. S., Libotte, G. B., & Platt, G. M. (2024). Multi-objective optimization of vibrating particle systems applied to engineering system design. Ciência E Natura, 46(esp. 1), e86556. https://doi.org/10.5902/2179460X86556

Issue

Vol. 46 No. esp. 1 (2024): ERMAC e ENMC

Section

Special Edition 1

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