Estudo de Sensibilidade do Algoritmo de Colônia de Vagalumes para um Problema de Engenharia Envolvendo Dimensionamento de Treliças

L. L. M. Pereira, D. C. Santos, M. H. M. Moraes, G. M. Gonçalves Filho, E. M. Ancioto Junior, W. M. Pereira Junior, M. J. P. Dantas

Abstract


A treliça é uma estrutura triangular rígida, com resistência aos esforços normais, podendo ser utilizada em telhados, mezaninos, torres de energia de telecomunicações e pontes. Logo é possível armar que esse sistema estrutural apresenta uma grande relevância no cenário da engenharia de estruturas. Nesta pesquisa é utilizado um método probabilístico de otimização global baseado em inteligência coletiva ou inteligência de enxame, com aplicações promissoras em diversos campos das ciências aplicadas, o Algoritmo de Colônia de Vagalumes (ACV), para determinação do peso mínimo de uma treliça de benchmark. Foi conduzida uma análise de sensibilidade com os parâmetros do algoritmo como: população (Npop), nímero de iterações (Ngen), parâmetro de aleatoriedade α, fator de atratividade β e parâmetro de absorção de luz (γ). A treliça utilizada nos testes foi uma estrutura de benchmark com 10 barras e essa foi otimizada obtendo um valor de peso mínimo em torno de 2284 kg, tal valor quando comparado a outros trabalhos da literatura mostram a efetividade do método adotado nesse trabalho. O software utilizado para as implementações e simulação das treliças foi o MATLAB.


Keywords


Optimization; Plain trusses; Steel Structures; Firefly Algorithm

References


Pintér JD. Global Optimization: Software, Test Problems, and Applications. In: Pardalos PM, Romeijn HE, editors. Handb. Glob. Optim., vol. 62, Boston, MA: Springer US; 2002, p. 515–69. doi:10.1007/978-1-4757-5362-2_15.

Łukasik S, Żak S. Firefly Algorithm for Continuous Constrained Optimization Tasks. In: Nguyen NT, Kowalczyk R, Chen S-M, editors. Comput. Collect. Intell. Semantic Web Soc. Netw. Multiagent Syst., vol. 5796, Berlin, Heidelberg: Springer Berlin Heidelberg; 2009, p. 97–106. doi:10.1007/978-3-642-04441-0_8.

Jaafari A, Razavi Termeh SV, Bui DT. Genetic and firefly metaheuristic algorithms for an optimized neuro-fuzzy prediction modeling of wildfire probability. J Environ Manage 2019;243:358–69. doi:10.1016/j.jenvman.2019.04.117.

Khalifehzadeh S, Fakhrzad MB. A modified firefly algorithm for optimizing a multi stage supply chain network with stochastic demand and fuzzy production capacity. Comput Ind Eng 2019;133:42–56. doi:10.1016/j.cie.2019.04.048.

La Scalia G, Micale R, Giallanza A, Marannano G. Firefly algorithm based upon slicing structure encoding for unequal facility layout problem. Int J Ind Eng Comput 2019:349–60. doi:10.5267/j.ijiec.2019.2.003.

Vishal P, Ramesh Babu A. Firefly Algorithm for Intelligent Context-Aware Sensor Deployment Problem in Wireless Sensor Network. J Circuits Syst Comput 2019;28:1950094. doi:10.1142/S0218126619500944.

Zhang J, Zhang Y, Ma Z. In silico Prediction of Human Secretory Proteins in Plasma Based on Discrete Firefly Optimization and Application to Cancer Biomarkers Identification. Front Genet 2019;10:542. doi:10.3389/fgene.2019.00542.

Zhang X, Jia W, Guan X, Xu G, Chen J, Zhu Y. Optimized deployment of a radar network based on an improved firefly algorithm. Front Inf Technol Electron Eng 2019;20:425–37. doi:10.1631/FITEE.1800749.

Guerra A, Kiousis PD. Design optimization of reinforced concrete structures. Comput Concr 2006;3:313–34. doi:10.12989/CAC.2006.3.5.313.

Singh RM. Design of Barrages with Genetic Algorithm Based Embedded Simulation Optimization Approach. Water Resour Manag 2011;25:409–29. doi:10.1007/s11269-010-9706-9.

Rana S, Islam N, Ahsan R, Ghani SN. Application of evolutionary operation to the minimum cost design of continuous prestressed concrete bridge structure. Eng Struct 2013;46:38–48. doi:10.1016/j.engstruct.2012.07.017.

Mousavi SS, Nikkhah M, Zare S. A comparative study of two meta-heuristic algorithms in optimizing cost of reinforced concrete segmental lining. J Min Environ 2018. doi:10.22044/jme.2018.7159.1566.

Camp CV, Bichon BJ, Stovall SP. Design of Steel Frames Using Ant Colony Optimization. J Struct Eng 2005;131:369–79. doi:10.1061/(ASCE)0733-9445(2005)131:3(369).

Jeong S, Seong HK, Kim CW, Yoo J. Structural design considering the uncertainty of load positions using the phase field design method. Finite Elem Anal Des 2019;161:1–15. doi:10.1016/j.finel.2019.04.002.

Salar M, Ghasemi MR, Dizangian B. Practical optimization of deployable and scissor-like structures using a fast GA method. Front Struct Civ Eng 2019;13:557–68. doi:10.1007/s11709-018-0497-z.

M. Salar, M. R. Ghasemi, and B. Dizangian, Practical optimization of deployable and scissor-like structures using a fast GA method, Frontiers of Structural

and Civil Engineering, vol. 13, pp. 557568, July 2018.

Di Cesare N, Domaszewski M. A new hybrid topology optimization method based on I-PR-PSO and ESO. Application to continuum structural mechanics. Comput Struct 2019;212:311–26. doi:10.1016/j.compstruc.2018.11.006.

Xu G, Liu B, Song J, Xiao S, Wu A. Multiobjective sorting-based learning particle swarm optimization for continuous optimization. Nat Comput 2019;18:313–31. doi:10.1007/s11047-016-9548-3.

Gholami K, Dehnavi E. A modified particle swarm optimization algorithm for scheduling renewable generation in a micro-grid under load uncertainty. Appl Soft Comput 2019;78:496–514. doi:10.1016/j.asoc.2019.02.042.

Yang X-S. Nature-Inspired Metaheuristic Algorithms. Luniver Press; 2008.

Wang H, Wang W, Zhou X, Sun H, Zhao J, Yu X, et al. Firefly algorithm with neighborhood attraction. Inf Sci 2017;382–383:374–87. doi:10.1016/j.ins.2016.12.024.

Carvalho CC. Desenvolvimento de um algoritmo de otimização evolutivo auto-adaptativo para a resolução de problemas de otimização com variáveis mistas. Dissertação. Universidade Federal de Goiás, 2018.

Gandomi AH, Yang X-S, Alavi AH. Mixed variable structural optimization using Firefly Algorithm. Comput Struct 2011;89:2325–36. doi:10.1016/j.compstruc.2011.08.002.

Yang X-S. Firefly Algorithm, Stochastic Test Functions and Design Optimisation. ArXiv10031409 Math 2010.

Yu S, Zhu S, Ma Y, Mao D. A variable step size firefly algorithm for numerical optimization. Appl Math Comput 2015;263:214–20. doi:10.1016/j.amc.2015.04.065.

Selvakumar B, Karuppiah M. Firefly algorithm based feature selection for network intrusion detection. Comput Secur 2019;81:148–55. doi:10.1016/j.cose.2018.11.005.

Talatahari S, Gandomi AH, Yun GJ. Optimum design of tower structures using Firefly Algorithm: OPTIMUM DESIGN OF TOWER STRUCTURES USING FIREFLY ALGORITHM. Struct Des Tall Spec Build 2014;23:350–61. doi:10.1002/tal.1043.

Sheikholeslami R, Khalili BG, Sadollah A, Kim J. Optimization of reinforced concrete retaining walls via hybrid firefly algorithm with upper bound strategy. KSCE J Civ Eng 2016;20:2428–38. doi:10.1007/s12205-015-1163-9.

Zhou G-D, Xie M-X, Yi T-H, Li H-N. Optimal wireless sensor network configuration for structural monitoring using automatic-learning firefly algorithm. Adv Struct Eng 2019;22:907–18. doi:10.1177/1369433218797074.

Farshi B, Alinia-ziazi A. Sizing optimization of truss structures by method of centers and force formulation. Int J Solids Struct 2010;47:2508–24. doi:10.1016/j.ijsolstr.2010.05.009.

Li LJ, Huang ZB, Liu F. A heuristic particle swarm optimization method for truss structures with discrete variables. Comput Struct 2009;87:435–43. doi:10.1016/j.compstruc.2009.01.004.

Aminifar F, Aminifar F, Nazarpour D. Optimal design of truss structures via an augmented genetic algorithm 2013:13. doi:doi:10.3906/muh-1203-13.

Camp CV, Farshchin M. Design of space trusses using modified teaching–learning based optimization. Eng Struct 2014;62–63:87–97. doi:10.1016/j.engstruct.2014.01.020.

Li LJ, Huang ZB, Liu F, Wu QH. A heuristic particle swarm optimizer for optimization of pin connected structures. Comput Struct 2007;85:340–9. doi:10.1016/j.compstruc.2006.11.020.




DOI: https://doi.org/10.5540/tema.2020.021.03.583

Article Metrics

Metrics Loading ...

Metrics powered by PLOS ALM

Refbacks

  • There are currently no refbacks.



Trends in Computational and Applied Mathematics

A publication of the Brazilian Society of Applied and Computational Mathematics (SBMAC)

 

Indexed in:

                       

         

 

Desenvolvido por:

Logomarca da Lepidus Tecnologia