Application of state-of-the-art multiobjective metaheuristic algorithms in reliability-based design optimization: a comparative study

Meng, Zeng; Yıldız, Betül Sultan; Li, Gang; Zhong, Changting; Mirjalili, Seyedali; Yıldız, Ali Rıza

doi:10.1007/s00158-023-03639-0

Cited by 56 publications

(4 citation statements)

References 190 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To address this issue, this paper introduces a variable that sets the spiral shape parameter l as a dynamic value that changes with the number of iterations, allowing whale individuals to dynamically adjust the spiral shape during the spiral search phase, enhancing the global search capability of the algorithm to improve its convergence accuracy. The improved strategy is shown in equations (10) (11) (12).…”

Section: F Improved Adaptive Spiral Strategy Of Whale Optimization Al...mentioning

confidence: 99%

“…Then, it entered the era of particle swarm optimization(PSO) [5] and differential evolution (DE) [6], where a large number of algorithms were subsequently developed and utilized. These include: grey wolf optimization algorithm [7], Symbiotic Organism Search Algorithm [8], cuckoo optimization algorithm [9], bat algorithm [10], hungry games search (HGS) algorithm [11], moth-flame optimization algorithm (MFO) [12], chaotic Levy flight distribution (CLFD) algorithm [13], cheetah optimization (CO) algorithm [14], and Henry gas solubility optimization algorithm (HGSO) [15] and so on. .…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A Novel Lightweight Multi-Objective Optimization Design System for Vehicle Chassis Frames Based on ANFIS-SHAMODE-IWOA Model

Minqing,

Hongxi,

Weihuan

et al. 2024

IEEE Access

View full text Add to dashboard Cite

In the process of daily product development and design, optimizing the shape and external dimensions of the vehicle chassis truss structure while considering both weight and reliability indicators often involves interdisciplinary collaboration and inefficient communication, leading to repetitive mechanical labor and low efficiency. This is widely regarded as a difficult and challenging task. In order to improve the design quality of the chassis truss structure and enhance work efficiency, this paper proposes a novel lightweight multi-objective optimization design system for vehicle chassis trusses based on the ANFIS-SHAMODE-IWOA model. Firstly, an adaptive spiral search strategy is introduced based on the multi-objective hybrid metaheuristic algorithm (SHAMODE) which is based on successful history. Then, a new SHAMODE-IWOA algorithm is proposed. In order to estimate the reliability level of the chassis truss structure under different design parameter combinations, a new ANFIS-SHAMODE-IWOA model is constructed by using the proposed SHAMODE-IWOA algorithm to learn the ANFIS model. Finally, in order to obtain the optimal design parameter combination, multi-objective optimization based on minimum design quality and optimal reliability measurement functions is studied using the SHAMODE-IWOA algorithm. Experimental results show that SHAMODE-IWOA has leading global optimization capability on CEC2017 test set benchmark functions. Compared with other intelligent models, the ANFIS-SHAMODE-IWOA model has better performance in reliability coefficient estimation. At the same time, the SHAMODE-IWOA algorithm obtains a more optimal design parameter combination for the chassis truss, with improvements of 9.5%, 12.5%, and 15% in Mass, Bending, and Torsion indicators, respectively. Finally, the proposed ANFIS-SHAMODE-IWOA multi-objective optimization design system, as a novel intelligent model, can be used to evaluate the reliability of chassis truss structures, improve development and design efficiency, and obtain the best design parameter combination, which is beneficial to improving the level of green intelligent manufacturing design.

show abstract

Section: F Improved Adaptive Spiral Strategy Of Whale Optimization Al...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Novel Lightweight Multi-Objective Optimization Design System for Vehicle Chassis Frames Based on ANFIS-SHAMODE-IWOA Model

Minqing,

Hongxi,

Weihuan

et al. 2024

IEEE Access

View full text Add to dashboard Cite

show abstract

“…Bhunia et al [31] proposed an efficient hybrid method based on GA and PSO for solving mixed integer non-linear RBDO problems in series, seriesparallel and bridge systems. Many other works have been developed by Zhong et al [32], Kaveh et al [33], Rashki et al [34], Meng et al [18,35,36], Sharma et al [18], Hamzahkolaei et al [37], Jafari-Asl et al [38], among others. Specially, Meng et al [12] comparatively analysed the application of the latest 10 metaheuristic algorithms in solving RBDO problems.…”

Section: Introductionmentioning

confidence: 99%

MECSBO: Multi‐strategy enhanced circulatory system based optimisation algorithm for global optimisation and reliability‐based design optimisation problems

Yang,

Guo,

Meng

et al. 2024

IET Collab Intel Manufact

View full text Add to dashboard Cite

The Circulatory System Based Optimisation (CSBO) stands as a nascent metaheuristic optimisation algorithm known for its proficiency in tackling global optimisation problems. The authors introduce the Multi‐strategy Enhanced CSBO (MECSBO), an algorithm designed for global optimisation and Reliability‐based Design Optimisation (RBDO). MECSBO integrates adaptive inertia weight, golden sine operator and chaos strategy to augment the convergence capacity and efficiency of the original CSBO. Furthermore, MECSBO‐based RBDO algorithm is presented to address RBDO problem. The comparative analysis utilising standard real‐world benchmark functions has been carried out to validate the effectiveness of the proposed MECSBO. Several RBDO problems, including three typical numerical examples and three engineering cases, are used to show abilities of the proposed MECSBO‐based RBDO algorithm. The results demonstrated that MECSBO is outperformed comparing to the state‐of‐the‐art algorithms in terms of accuracy, efficiency, and robustness in RBDO problems.

show abstract

“…Several MOEAs were proposed in the literature to solve MOSOPs. Recently, several works were addressed to solve structural optimization problems, such as those of Tejani et al [26], Kumar et al [27], Jafari et al [28], Eid et al [29], Khodadadi et al [30], Jelovica and Cai [31], Kumar et al [32], Sadeeq and Abdulazeez [33], Zhong et al [34], and Meng et al [35]. Additional references about new methodologies and approaches, MOSOPs, MOEAs, and new approaches can be found in [24].…”

mentioning

confidence: 99%

Automatic Column Grouping of 3D Steel Frames via Multi-Objective Structural Optimization

Resende,

Martha,

Lemonge

et al. 2024

Buildings

View full text Add to dashboard Cite

Formulations of structural optimization problems are proposed in this paper to automatically find the best grouping of columns in 3D steel buildings. In these formulations, the conflicting objective functions, minimized simultaneously, are the weight of the structure and the number of different groups of columns. In other words, the smaller the number of different groups of columns, the greater the weight of the structure, and the greater the number of groups, the smaller the structure’s weight. The design variables are the bracing system configuration, column cross-section orientation, and assigned W-shaped profile indices for columns, beams, and braces. The design constraints are the allowable displacements, strength, and geometric considerations. After solving the multi-objective optimization problem, the result is a Pareto front, presenting non-dominated solutions. Three evolutionary algorithms based on differential evolution are adopted in this paper to solve three computational experiments. Even if preliminary groupings of columns are adopted, considering architectural aspects such as the symmetry of the structure, it is possible to discover other interesting structural configurations that will be available to the decision maker, who will be able to make their choices based on the impacts on manufacturing, cutting, transporting, checking and welding.

show abstract

Application of state-of-the-art multiobjective metaheuristic algorithms in reliability-based design optimization: a comparative study

Cited by 56 publications

References 190 publications

A Novel Lightweight Multi-Objective Optimization Design System for Vehicle Chassis Frames Based on ANFIS-SHAMODE-IWOA Model

A Novel Lightweight Multi-Objective Optimization Design System for Vehicle Chassis Frames Based on ANFIS-SHAMODE-IWOA Model

MECSBO: Multi‐strategy enhanced circulatory system based optimisation algorithm for global optimisation and reliability‐based design optimisation problems

Automatic Column Grouping of 3D Steel Frames via Multi-Objective Structural Optimization

Contact Info

Product

Resources

About