OPTIMIZATION OF STIFFENED COMPOSITE PLATE USING BALANCING COMPOSITE MOTION OPTIMIZATION
Article Sidebar
Published:
Jul 20, 2023
Keywords:
balancing Composite Motion Optimization (BCMO), metaheuristic algorithm, optimization analysis, stiffened composite plate
Main Article Content
Abstract
Recently, metaheuristic optimization algorithms have been studied and applied in many fields of engineering, especially in solving structural optimization problems. For structures with complex behaviors, the selection of a suitable optimization algorithm significantly increases the computational efficiency and the accuracy of the solution. In this paper, we investigate the optimization problem of stiffened composite plates using Balancing Composite Motion Optimization. The core idea of the Balancing Composite Motion Optimization algorithm is that the searching movements of candidate solutions are compositely equalized in both global and local ones in the solution space of solving the fiber optimization problem of stiffened composite plates. A candidate solution can move closer to better ones to exploit the local regions and move further to explore the search space also. The method does not require algorithm parameters. The calculation results are compared with many other metaheuristic optimization methods to prove the accuracy and efficiency of the method.
Downloads
Download data is not yet available.
Article Details
How to Cite
1.
Nguyen S, Lam P, Trieu V, Huynh S. OPTIMIZATION OF STIFFENED COMPOSITE PLATE USING BALANCING COMPOSITE MOTION OPTIMIZATION. journal [Internet]. 20Jul.2023 [cited 19May2024];13(6). Available from: https://journal.tvu.edu.vn/index.php/journal/article/view/2129
Section
Articles
References
[1] Hwang SF, Hsu YC, Chen Y. A genetic algorithm for the optimization of fiber angles
in composite laminates. Journal of Mechanical Science and Technology. 2014;28: 3163–3169.
https://doi.org/10.1007/s12206-014-0725-y.
[2] Marín L, Trias D, Badalló P, Rus G, Mayugo
JA. Optimization of composite stiffened panels
under mechanical and hygrothermal loads
using neural networks and genetic algorithms.
Composite Structures. 2012;94(11): 3321–3326.
https://doi.org/10.1016/j.compstruct.2012.04.024.
[3] Falzon BG, Faggiani A. The use of a genetic algorithm to improve the postbuckling strength of stiffened composite panels susceptible to secondary instabilities. Composite Structures. 2012;94(3), 883–895.
https://doi.org/10.1016/j.compstruct.2011.10.015.
[4] T. Nguyen-Thoi, V. Ho-Huu, H. Dang-Trung, T.
Bui-Xuan, and T. Lam-Phat. Optimization analysis
of stiffened composite plate by sequential quadratic
programming. Journal of Science and Technology.
2013;51(4B): 156–165.
[5] Nguyen-Thoi T, Phung-Van P, Nguyen-Xuan H,
Thai-Hoang C. A cell-based smoothed discrete shear
gap method using triangular elements for static
and free vibration analyses of Reissner–Mindlin
plates. International Journal for Numerical
Methods in Engineering. 2012;91(7): 705–741.
https://doi.org/10.1002/nme.4289.
[6] Bui Xuan Thang, Nguyen Thoi Trung, Pham-Duc
Tuan, Phung Van Phuc, Ngo-Thanh Phong. An analysis of eccentrically stiffened plates by CS-DSG3
using triangular elements. [Dự phân tích các tấm được
gia cường độ cứng lệch bởi CS-DSG3 sử dụng các
phần tử tam giác] In: The International Conference
on Advances in Computational Mechanics (ACOME
2012), Ton Duc Thang University, [Hội nghị Quốc tế
về Tiến bộ trong Cơ học Tính toán (ACOME 2012),
Trường Đại học Tôn Đức Thắng] August 14 - 16
2012. Ho Chi Minh City, Vietnam: Ton Duc Thang
University; 2012. p.629–643.
[7] Sastry K, Goldberg DE, Kendall G. Genetic Algorithms. In: Burke EK, Kendall G. (eds.) Search
Methodologies. Boston, MA: Springer; 2014. p.93-
117. https://doi.org/10.1007/978-1-4614-6940-7_4.
[8] Eberhart R, Kennedy J. A new optimizer using particle swarm theory. In: MHS’95. Proceedings of the
Sixth International Symposium on Micro Machine and
Human Science, Nagoya, Japan. IEEE; 1995. p. 39–
43. http://dx.doi.org/10.1109/MHS.1995.494215.
[9] Storn R, Price K. Differential evolution –
A simple and efficient heuristic for global
optimization over continuous spaces. Journal
of Global Optimization. 1997;11: 341–359.
https://doi.org/10.1023/A:1008202821328.
[10] Wang Z, Tang H, Li P. Optimum design of
truss structures based on differential evolution
strategy. In: 2009 International Conference
on Information Engineering and Computer
Science, Wuhan, China. IEEE; 2009. p.1–5.
http://dx.doi.org/10.1109/ICIECS.2009.5365996.
[11] Wu CY, Tseng KY. Truss structure optimization
using adaptive multi-population differential evolution. Structural and Multidisciplinary Optimization.
2010;42: 575–590. https://doi.org/10.1007/s00158-
010-0507-9.
[12] Le-Anh L, Nguyen-Thoi T, Ho-Huu V, DangTrung H, Bui-Xuan T. Static and frequency
optimization of folded laminated composite plates using an adjusted differential evolution
algorithm and a smoothed triangular plate
element. Composite Structures. 2015;127: 382–394.
https://doi.org/10.1016/j.compstruct.2015.02.069.
[13] Ho-Huu V, Nguyen-Thoi T, Nguyen-Thoi MH, LeAnh L. An improved constrained differential evolution using discrete variables (D-ICDE) for layout optimization of truss structures. Expert Systems with Applications. 2015;2(20): 7057–7069.
https://doi.org/10.1016/j.eswa.2015.04.072.
[14] V. Ho-Huu, T. Nguyen-Thoi, T. Khac-Truong, L.
Le-Anh, and M. H. Nguyen-Thoi. A fast efficient differential evolution based on roulette
wheel selection for shape and sizing optimization of truss with frequency constraints. 2015.
https://www.researchgate.net/publication/304752798
_An_efficient_differential_evolution_based_on
_roulette_wheel_selection_for_shape_and
_sizing_optimization_of_truss_with_frequency
_constraint [Accessed 20th March 2023].
[15] Khaparde AR, Alassery F, Kumar A, Alotaibi Y,
Khalaf OI, Pillai S, Alghamdi S. Differential
evolution algorithm with hierarchical fair
competition model. Intelligent Automation
& Soft Computing. 2022;33(2): 1045–1062.
http://dx.doi.org/10.32604/iasc.2022.023270.
[16] Yang XS. Firefly algorithms for multimodal optimization. In: Watanabe O, Zeugmann T. (eds.) Stochastic
Algorithms: Foundations and Applications. Berlin,
Heidelberg: Springer Berlin Heidelberg. 2009. p.169–
178. https://doi.org/10.1007/978-3-642-04944-6_14.
[17] Parvathi S, Umamaheswari S. Discrete Firefly Algorithm for Optimizing Topology Generation and
Core Mapping of Network-on-Chip. Intelligent Automation & Soft Computing. 2022;34(1): 15–32.
http://dx.doi.org/10.32604/iasc.2022.025290.
[18] Dorigo M, Maniezzo V, Colorni A. Ant
system: optimization by a colony of cooperating
agents. IEEE Transactions on Systems, Man,
and Cybernetics: Systems. 1996;26(1): 29–41.
http://dx.doi.org/10.1109/3477.484436.
[19] Neri F, Cotta C. Memetic algorithms and memetic
computing optimization: A literature review. Swarm
and Evolutionary Computation. 2012;2: 1–14.
https://doi.org/10.1016/j.swevo.2011.11.003.
[20] Mirjalili S. Moth-flame optimization algorithm:
A novel nature-inspired heuristic paradigm.
Knowledge-Based Systems. 2015;89: 228–249.
https://doi.org/10.1016/j.knosys.2015.07.006.
[21] Rashedi E, Nezamabadi-Pour H, Saryazdi
S. GSA: a gravitational search algorithm.
Information Sciences. 2009;179(13): 2232–2248.
https://doi.org/10.1016/j.ins.2009.03.004.
[22] Rao R. Jaya: A simple and new optimization algorithm for solving constrained and unconstrained
optimization problems. International Journal of Industrial Engineering Computations. 2016;7(1): 19–
34. http://dx.doi.org/10.5267/j.ijiec.2015.8.004.
[23] Lam-Phat T, Ho-Huu V, Nguyen-Ngoc S, NguyenHoai S, Nguyen-Thoi T. Deterministic and reliabilitybased lightweight design of Timoshenko composite
beams. Engineering with Computers. 2021;37: 2329–
2344. https://doi.org/10.1007/s00366-020-00946-8.
[24] Kar AK. Bio inspired computing–a review of
algorithms and scope of applications. Expert
Systems with Applications. 2016;59: 20–32.
https://doi.org/10.1016/j.eswa.2016.04.018.
[25] Le-Duc T, Ho-Huu V, Nguyen-Quoc H. Multiobjective optimal design of magnetorheological
brakes for motorcycling application considering
thermal effect in working process. Smart
Materials and Structures. 2018;27(7): 075060.
http://dx.doi.org/10.1088/1361-665X/aacb40.
[26] Le DT, Bui DK, Ngo TD, Nguyen QH,
Nguyen-Xuan H. A novel hybrid method
combining electromagnetism-like mechanism
and firefly algorithms for constrained design
optimization of discrete truss structures.
Computers & Structures. 2019;212: 20–42.
https://doi.org/10.1016/j.compstruc.2018.10.017.
[27] Le-Duc T, Ho-Huu V, Nguyen-Thoi T, Nguyen-Quoc
H. A new design approach based on differential evolution algorithm for geometric optimization of magnetorheological brakes. Smart Materials and Structures.
2016;25(12): 125020. http://dx.doi.org/10.1088/0964-
1726/25/12/125020.
[28] Yang XS. Optimization techniques and applications
with examples. New Jersey, United States of America:
John Wiley & Sons; 2018.
[29] Le-Duc T, Nguyen QH, Nguyen-Xuan H.
Balancing composite motion optimization.
Information Sciences. 2020;520: 250–270.
https://doi.org/10.1016/j.ins.2020.02.013.
[30] Duong HT, Phan HC, Le TT, Bui ND. Optimization
design of rectangular concrete-filled steel tube short
columns with Balancing Composite Motion Optimization and data-driven model. Structures. 2020;28:
757–765. https://doi.org/10.1016/j.istruc.2020.09.013
[31] Duong HT, Le TT, Nguyen XS, Le MV, Phan HC, Le
LM, et al. Balancing composite motion optimization
and artificial neural network for the prediction of
critical load of concrete-filled steel tubes under axial
compression. In: Nguyen DC, Vu NP, Long BT,
Puta H, Sattler KU. (eds.) Advances in Engineering
Research and Application. Cham: Springer; 2022.
p.290–296. https://doi.org/10.1007/978-3-031-22200-9_31.
[32] Kolli M, Chandrashekhara K. Finite element analysis
of stiffened laminated plates under transverse loading.
Composites Science and Technology. 1996;56(12):
1355–1361. https://doi.org/10.1016/S0266-
3538(96)00086-3.
[33] Li L, Xiaohui R. Stiffened plate bending analysis
in terms of refined triangular laminated plate element. Composite Structures. 2010;92(12): 2936-2945.
https://doi.org/10.1016/j.compstruct.2010.05.005.
[34] Lam-Phat T, Nguyen-Hoai S, Ho-Huu V, NguyenThoi T. Optimization of stiffened composite plate using adjusted different evolution algorithm. In: The 7th
International Conference on Computational Methods
(ICCM2016). Berkeley, CA, USA: 2016.
in composite laminates. Journal of Mechanical Science and Technology. 2014;28: 3163–3169.
https://doi.org/10.1007/s12206-014-0725-y.
[2] Marín L, Trias D, Badalló P, Rus G, Mayugo
JA. Optimization of composite stiffened panels
under mechanical and hygrothermal loads
using neural networks and genetic algorithms.
Composite Structures. 2012;94(11): 3321–3326.
https://doi.org/10.1016/j.compstruct.2012.04.024.
[3] Falzon BG, Faggiani A. The use of a genetic algorithm to improve the postbuckling strength of stiffened composite panels susceptible to secondary instabilities. Composite Structures. 2012;94(3), 883–895.
https://doi.org/10.1016/j.compstruct.2011.10.015.
[4] T. Nguyen-Thoi, V. Ho-Huu, H. Dang-Trung, T.
Bui-Xuan, and T. Lam-Phat. Optimization analysis
of stiffened composite plate by sequential quadratic
programming. Journal of Science and Technology.
2013;51(4B): 156–165.
[5] Nguyen-Thoi T, Phung-Van P, Nguyen-Xuan H,
Thai-Hoang C. A cell-based smoothed discrete shear
gap method using triangular elements for static
and free vibration analyses of Reissner–Mindlin
plates. International Journal for Numerical
Methods in Engineering. 2012;91(7): 705–741.
https://doi.org/10.1002/nme.4289.
[6] Bui Xuan Thang, Nguyen Thoi Trung, Pham-Duc
Tuan, Phung Van Phuc, Ngo-Thanh Phong. An analysis of eccentrically stiffened plates by CS-DSG3
using triangular elements. [Dự phân tích các tấm được
gia cường độ cứng lệch bởi CS-DSG3 sử dụng các
phần tử tam giác] In: The International Conference
on Advances in Computational Mechanics (ACOME
2012), Ton Duc Thang University, [Hội nghị Quốc tế
về Tiến bộ trong Cơ học Tính toán (ACOME 2012),
Trường Đại học Tôn Đức Thắng] August 14 - 16
2012. Ho Chi Minh City, Vietnam: Ton Duc Thang
University; 2012. p.629–643.
[7] Sastry K, Goldberg DE, Kendall G. Genetic Algorithms. In: Burke EK, Kendall G. (eds.) Search
Methodologies. Boston, MA: Springer; 2014. p.93-
117. https://doi.org/10.1007/978-1-4614-6940-7_4.
[8] Eberhart R, Kennedy J. A new optimizer using particle swarm theory. In: MHS’95. Proceedings of the
Sixth International Symposium on Micro Machine and
Human Science, Nagoya, Japan. IEEE; 1995. p. 39–
43. http://dx.doi.org/10.1109/MHS.1995.494215.
[9] Storn R, Price K. Differential evolution –
A simple and efficient heuristic for global
optimization over continuous spaces. Journal
of Global Optimization. 1997;11: 341–359.
https://doi.org/10.1023/A:1008202821328.
[10] Wang Z, Tang H, Li P. Optimum design of
truss structures based on differential evolution
strategy. In: 2009 International Conference
on Information Engineering and Computer
Science, Wuhan, China. IEEE; 2009. p.1–5.
http://dx.doi.org/10.1109/ICIECS.2009.5365996.
[11] Wu CY, Tseng KY. Truss structure optimization
using adaptive multi-population differential evolution. Structural and Multidisciplinary Optimization.
2010;42: 575–590. https://doi.org/10.1007/s00158-
010-0507-9.
[12] Le-Anh L, Nguyen-Thoi T, Ho-Huu V, DangTrung H, Bui-Xuan T. Static and frequency
optimization of folded laminated composite plates using an adjusted differential evolution
algorithm and a smoothed triangular plate
element. Composite Structures. 2015;127: 382–394.
https://doi.org/10.1016/j.compstruct.2015.02.069.
[13] Ho-Huu V, Nguyen-Thoi T, Nguyen-Thoi MH, LeAnh L. An improved constrained differential evolution using discrete variables (D-ICDE) for layout optimization of truss structures. Expert Systems with Applications. 2015;2(20): 7057–7069.
https://doi.org/10.1016/j.eswa.2015.04.072.
[14] V. Ho-Huu, T. Nguyen-Thoi, T. Khac-Truong, L.
Le-Anh, and M. H. Nguyen-Thoi. A fast efficient differential evolution based on roulette
wheel selection for shape and sizing optimization of truss with frequency constraints. 2015.
https://www.researchgate.net/publication/304752798
_An_efficient_differential_evolution_based_on
_roulette_wheel_selection_for_shape_and
_sizing_optimization_of_truss_with_frequency
_constraint [Accessed 20th March 2023].
[15] Khaparde AR, Alassery F, Kumar A, Alotaibi Y,
Khalaf OI, Pillai S, Alghamdi S. Differential
evolution algorithm with hierarchical fair
competition model. Intelligent Automation
& Soft Computing. 2022;33(2): 1045–1062.
http://dx.doi.org/10.32604/iasc.2022.023270.
[16] Yang XS. Firefly algorithms for multimodal optimization. In: Watanabe O, Zeugmann T. (eds.) Stochastic
Algorithms: Foundations and Applications. Berlin,
Heidelberg: Springer Berlin Heidelberg. 2009. p.169–
178. https://doi.org/10.1007/978-3-642-04944-6_14.
[17] Parvathi S, Umamaheswari S. Discrete Firefly Algorithm for Optimizing Topology Generation and
Core Mapping of Network-on-Chip. Intelligent Automation & Soft Computing. 2022;34(1): 15–32.
http://dx.doi.org/10.32604/iasc.2022.025290.
[18] Dorigo M, Maniezzo V, Colorni A. Ant
system: optimization by a colony of cooperating
agents. IEEE Transactions on Systems, Man,
and Cybernetics: Systems. 1996;26(1): 29–41.
http://dx.doi.org/10.1109/3477.484436.
[19] Neri F, Cotta C. Memetic algorithms and memetic
computing optimization: A literature review. Swarm
and Evolutionary Computation. 2012;2: 1–14.
https://doi.org/10.1016/j.swevo.2011.11.003.
[20] Mirjalili S. Moth-flame optimization algorithm:
A novel nature-inspired heuristic paradigm.
Knowledge-Based Systems. 2015;89: 228–249.
https://doi.org/10.1016/j.knosys.2015.07.006.
[21] Rashedi E, Nezamabadi-Pour H, Saryazdi
S. GSA: a gravitational search algorithm.
Information Sciences. 2009;179(13): 2232–2248.
https://doi.org/10.1016/j.ins.2009.03.004.
[22] Rao R. Jaya: A simple and new optimization algorithm for solving constrained and unconstrained
optimization problems. International Journal of Industrial Engineering Computations. 2016;7(1): 19–
34. http://dx.doi.org/10.5267/j.ijiec.2015.8.004.
[23] Lam-Phat T, Ho-Huu V, Nguyen-Ngoc S, NguyenHoai S, Nguyen-Thoi T. Deterministic and reliabilitybased lightweight design of Timoshenko composite
beams. Engineering with Computers. 2021;37: 2329–
2344. https://doi.org/10.1007/s00366-020-00946-8.
[24] Kar AK. Bio inspired computing–a review of
algorithms and scope of applications. Expert
Systems with Applications. 2016;59: 20–32.
https://doi.org/10.1016/j.eswa.2016.04.018.
[25] Le-Duc T, Ho-Huu V, Nguyen-Quoc H. Multiobjective optimal design of magnetorheological
brakes for motorcycling application considering
thermal effect in working process. Smart
Materials and Structures. 2018;27(7): 075060.
http://dx.doi.org/10.1088/1361-665X/aacb40.
[26] Le DT, Bui DK, Ngo TD, Nguyen QH,
Nguyen-Xuan H. A novel hybrid method
combining electromagnetism-like mechanism
and firefly algorithms for constrained design
optimization of discrete truss structures.
Computers & Structures. 2019;212: 20–42.
https://doi.org/10.1016/j.compstruc.2018.10.017.
[27] Le-Duc T, Ho-Huu V, Nguyen-Thoi T, Nguyen-Quoc
H. A new design approach based on differential evolution algorithm for geometric optimization of magnetorheological brakes. Smart Materials and Structures.
2016;25(12): 125020. http://dx.doi.org/10.1088/0964-
1726/25/12/125020.
[28] Yang XS. Optimization techniques and applications
with examples. New Jersey, United States of America:
John Wiley & Sons; 2018.
[29] Le-Duc T, Nguyen QH, Nguyen-Xuan H.
Balancing composite motion optimization.
Information Sciences. 2020;520: 250–270.
https://doi.org/10.1016/j.ins.2020.02.013.
[30] Duong HT, Phan HC, Le TT, Bui ND. Optimization
design of rectangular concrete-filled steel tube short
columns with Balancing Composite Motion Optimization and data-driven model. Structures. 2020;28:
757–765. https://doi.org/10.1016/j.istruc.2020.09.013
[31] Duong HT, Le TT, Nguyen XS, Le MV, Phan HC, Le
LM, et al. Balancing composite motion optimization
and artificial neural network for the prediction of
critical load of concrete-filled steel tubes under axial
compression. In: Nguyen DC, Vu NP, Long BT,
Puta H, Sattler KU. (eds.) Advances in Engineering
Research and Application. Cham: Springer; 2022.
p.290–296. https://doi.org/10.1007/978-3-031-22200-9_31.
[32] Kolli M, Chandrashekhara K. Finite element analysis
of stiffened laminated plates under transverse loading.
Composites Science and Technology. 1996;56(12):
1355–1361. https://doi.org/10.1016/S0266-
3538(96)00086-3.
[33] Li L, Xiaohui R. Stiffened plate bending analysis
in terms of refined triangular laminated plate element. Composite Structures. 2010;92(12): 2936-2945.
https://doi.org/10.1016/j.compstruct.2010.05.005.
[34] Lam-Phat T, Nguyen-Hoai S, Ho-Huu V, NguyenThoi T. Optimization of stiffened composite plate using adjusted different evolution algorithm. In: The 7th
International Conference on Computational Methods
(ICCM2016). Berkeley, CA, USA: 2016.