Bi-Objective Optimisation of Architecturally Constrained Column Layout Design: Strain Energy vs. The Number of Columns DOI

B. Pollock,

Elena Atroshchenko, Hossein Goudarzi

et al.

Published: Jan. 1, 2025

Language: Английский

Application of the 2-archive multi-objective cuckoo search algorithm for structure optimization DOI Creative Commons
Ghanshyam G. Tejani, Nikunj Mashru, Pinank Patel

et al.

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: Dec. 30, 2024

The study suggests a better multi-objective optimization method called 2-Archive Multi-Objective Cuckoo Search (MOCS2arc). It is then used to improve eight classical truss structures and six ZDT test functions. aims minimize both mass compliance simultaneously. MOCS2arc an advanced version of the traditional (MOCS) algorithm, enhanced through dual archive strategy that significantly improves solution diversity performance. To evaluate effectiveness MOCS2arc, we conducted extensive comparisons with several established algorithms: MOSCA, MODA, MOWHO, MOMFO, MOMPA, NSGA-II, DEMO, MOCS. Such comparison has been made various performance metrics compare benchmark efficacy proposed algorithm. These comprehensively assess algorithms' abilities generate diverse optimal solutions. statistical results demonstrate superior evidenced by Additionally, Friedman's & Wilcoxon's corroborate finding consistently delivers compared others. show highly effective improved algorithm for structure optimization, offering significant promising improvements over existing methods.

Language: Английский

Citations

19
MORIME: A Multi-Objective RIME Optimization Framework for Efficient Truss Design DOI Creative Commons
Mohammad Aljaidi, Nikunj Mashru, Pinank Patel

et al.

Results in Engineering, Journal Year: 2025, Volume and Issue: 25, P. 103933 - 103933

Published: Jan. 5, 2025

Language: Английский

Citations

8
Reliability-based multi-objective optimization of trusses with greylag goose algorithm DOI
Nikunj Mashru, Ghanshyam G. Tejani, Pinank Patel

et al.

Evolutionary Intelligence, Journal Year: 2025, Volume and Issue: 18(1)

Published: Jan. 9, 2025

Language: Английский

Citations

6
Enhancing heart disease classification based on greylag goose optimization algorithm and long short-term memory DOI Creative Commons
Ahmed M. Elshewey, Amira Hassan Abed, Doaa Sami Khafaga

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: Jan. 8, 2025

Heart disease is a category of various conditions that affect the heart, which includes multiple diseases influence its structure and operation. Such may consist coronary artery disease, characterized by narrowing or clotting arteries supply blood to heart muscle, with resulting threat attacks. rhythm disorders (arrhythmias), valve problems, congenital defects present at birth, muscle (cardiomyopathies) are other types disease. The objective this work introduce Greylag Goose Optimization (GGO) algorithm, seeks improve accuracy classification. GGO algorithm's binary format specifically intended choose most effective set features can classification when compared six optimization algorithms. bGGO algorithm for selecting optimal enhance accuracy. phase utilizes many classifiers, findings indicated Long Short-Term Memory (LSTM) emerged as classifier, achieving an rate 91.79%. hyperparameter LSTM model tuned using GGO, outcome alternative optimizers. obtained highest performance, 99.58%. statistical analysis employed Wilcoxon signed-rank test ANOVA assess feature selection outcomes. Furthermore, visual representations results was provided confirm robustness effectiveness proposed hybrid approach (GGO + LSTM).

Language: Английский

Citations

5
Performance analysis of hybrid optimization approach for UAV path planning control using FOPID-TID controller and HAOAROA algorithm DOI Creative Commons
Noorulden Basil,

Abdullah Fadhil Mohammed,

Bayan Mahdi Sabbar

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: Feb. 9, 2025

In this study, we present a comparative analysis of various trajectory optimization algorithms for Unmanned Aerial Vehicles (UAVs) navigating complex environments. The performance the proposed FOPID-TID based HAOAROA (Hybrid Archimedes Optimization Algorithm-Rider Algorithm) is evaluated against traditional methods such as A*, JPS, Bezier, and L-BSGF algorithms. approach integrates advantages fractional-order control with hybrid techniques to improve UAV planning. Simulation results indicate that method carries significantly better than respect length, smoothness, overall stability. Remarkably, yields 10% reduced length smoother while also being more computationally efficient. By using parameters, dynamic response becomes in challenging This shows disturbance rejection precision are much superior original two subroutines. applications presented study allow future growth system improvements provide proof concept improving UAVs dynamic,

Language: Английский

Citations

5
Optimization of truss structures with two archive-boosted MOHO algorithm DOI
Ghanshyam G. Tejani, Sunil Kumar Sharma, Nikunj Mashru

et al.

Alexandria Engineering Journal, Journal Year: 2025, Volume and Issue: 120, P. 296 - 317

Published: Feb. 18, 2025

Language: Английский

Citations

5
An efficient archive-based parameter-free multi-objective Rao-DE algorithm for bi-objective optimization of truss structures DOI
Viet-Hung Truong, Sawekchai Tangaramvong, Hoang-Anh Pham

et al.

Computers & Structures, Journal Year: 2025, Volume and Issue: 308, P. 107647 - 107647

Published: Jan. 8, 2025

Language: Английский

Citations

4
Mirage search optimization: Application to path planning and engineering design problems DOI
Jiahao He, Shijie Zhao,

Jiayi Ding

et al.

Advances in Engineering Software, Journal Year: 2025, Volume and Issue: 203, P. 103883 - 103883

Published: Feb. 18, 2025

Language: Английский

Citations

4
Advancing Truss Structure Optimization— A Multi-Objective Weighted Average Algorithm with Enhanced Convergence and Diversity DOI Creative Commons

Divya Adalja,

Kanak Kalita, Lenka Čepová

et al.

Results in Engineering, Journal Year: 2025, Volume and Issue: unknown, P. 104241 - 104241

Published: Feb. 1, 2025

Language: Английский

Citations

3
MOBBO: A Multiobjective Brown Bear Optimization Algorithm for Solving Constrained Structural Optimization Problems DOI Creative Commons
Pranav Mehta, Sumit Kumar, Ghanshyam G. Tejani

et al.

Journal of Optimization, Journal Year: 2024, Volume and Issue: 2024(1)

Published: Jan. 1, 2024

The multiobjective (MO) optimizers show great promise in solving constrained engineering structural problems. This paper introduces a MO version of the Brown Bear Optimization (BBO) algorithm, inspired by foraging behavior brown bears. proposed Multiobjective (MOBBO) algorithm is applied to five optimization problems, including 10‐bar, 25‐bar, 60‐bar, 72‐bar, and 942‐bar trusses, aiming minimize both mass maximum nodal deflection simultaneously. Comparative evaluations against six benchmark algorithms demonstrate MOBBO’s superior convergence, solution diversity, effectiveness addressing highly hypervolume (HV) inverted generational distance (IGD) metrics place MOBBO first rank according Friedman test, with an average standard deviation 0.0002. Moreover, spacing‐to‐extent (STE) (GD) second. final test highlights overall dominance, achieving rank. Best Pareto plots, diversity graphs, box plot analyses further suggest performance convergence compared existing algorithms. Therefore, can be effectively various tasks industry, offering refined global solutions contributing valuable insights field

Language: Английский

Citations

12