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Structural design using multi-objective metaheuristics. Comparative study and application to a real-world problem

Authors:

Gustavo Zavala,

Antonio J. Nebro,

Francisco Luna,

Carlos A. Coello CoelloAuthors Info & Claims

Structural and Multidisciplinary Optimization, Volume 53, Issue 3

Pages 545 - 566

https://doi.org/10.1007/s00158-015-1291-3

Published: 01 March 2016 Publication History

Abstract

Many structural design problems in the field of civil engineering are naturally multi-criteria, i.e., they have several conflicting objectives that have to be optimized simultaneously. An example is when we aim to reduce the weight of a structure while enhancing its robustness. There is no a single solution to these types of problems, but rather a set of designs representing trade-offs among the conflicting objectives. This paper focuses on the application of multi-objective metaheuristics to solve two variants of a real-world structural design problem. The goal is to compare a representative set of state-of-the-art multi-objective metaheuristic algorithms aiming to provide civil engineers with hints as to what optimization techniques to use when facing similar problems as those selected in the study presented in this paper. Accordingly, our study reveals that MOCell, a cellular genetic algorithm, provides the best overall performance, while NSGA-II, the de facto standard multi-objective metaheuristic technique, also demonstrates a competitive behavior.

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Cited By

Li GZhang TTsai CYao LLu YTang J(2024)Review of the metaheuristic algorithms in applicationsExpert Systems with Applications: An International Journal10.1016/j.eswa.2024.124857255:PDOnline publication date: 21-Nov-2024
https://dl.acm.org/doi/10.1016/j.eswa.2024.124857
Cao PZhang YZhou KTang J(2022)A reinforcement learning hyper-heuristic in multi-objective optimization with application to structural damage identificationStructural and Multidisciplinary Optimization10.1007/s00158-022-03432-566:1Online publication date: 28-Dec-2022
https://dl.acm.org/doi/10.1007/s00158-022-03432-5
Ramírez ARomero JGarcía-Martínez CVentura S(2019)JCLEC-MOEngineering Applications of Artificial Intelligence10.1016/j.engappai.2019.02.00381:C(14-28)Online publication date: 1-May-2019
https://dl.acm.org/doi/10.1016/j.engappai.2019.02.003

Structural design using multi-objective metaheuristics. Comparative study and application to a real-world problem
1. Information systems
  1. Data management systems
    1. Database administration
2. Theory of computation
  1. Design and analysis of algorithms

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Published In

cover image Structural and Multidisciplinary Optimization

Structural and Multidisciplinary Optimization Volume 53, Issue 3

March 2016

264 pages

ISSN:1615-147X

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Copyright © Copyright © 2016 Springer-Verlag Berlin Heidelberg.

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Springer-Verlag

Berlin, Heidelberg

Publication History

Published: 01 March 2016

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Cited By

Li GZhang TTsai CYao LLu YTang J(2024)Review of the metaheuristic algorithms in applicationsExpert Systems with Applications: An International Journal10.1016/j.eswa.2024.124857255:PDOnline publication date: 21-Nov-2024
https://dl.acm.org/doi/10.1016/j.eswa.2024.124857
Cao PZhang YZhou KTang J(2022)A reinforcement learning hyper-heuristic in multi-objective optimization with application to structural damage identificationStructural and Multidisciplinary Optimization10.1007/s00158-022-03432-566:1Online publication date: 28-Dec-2022
https://dl.acm.org/doi/10.1007/s00158-022-03432-5
Ramírez ARomero JGarcía-Martínez CVentura S(2019)JCLEC-MOEngineering Applications of Artificial Intelligence10.1016/j.engappai.2019.02.00381:C(14-28)Online publication date: 1-May-2019
https://dl.acm.org/doi/10.1016/j.engappai.2019.02.003

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