Nonlinear dynamic analysis of the bridge bearing and genetic algorithm–based optimization for seismic mitigation

Liang, Xuan; Cheng, Lin; Liu, Tianqiao; Du, Jiuyu

doi:10.1177/1369433220916936

Cited by 5 publications

(3 citation statements)

References 40 publications

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“…For example, Jin [61] adopted a genetic algorithm as the core to develop an intelligent logistics supply chain management system. Furthermore, genetic algorithms are also suitable for both linear and non-linear problems [62,63]. Chen et al [64] used a genetic algorithm to solve a multi-objective mixed-integer non-linear programming model for a sustainable reverse logistics network.…”

Section: Applications Of Genetic Algorithms In Logistics and Supply C...mentioning

confidence: 99%

A Bibliometric Analysis of a Genetic Algorithm for Supply Chain Agility

Lam,

Lee

2024

Mathematics

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As a famous population-based metaheuristic algorithm, a genetic algorithm can be used to overcome optimization complexities. A genetic algorithm adopts probabilistic transition rules and is suitable for parallelism, which makes this algorithm attractive in many areas, including the logistics and supply chain sector. To obtain a comprehensive understanding of the development in this area, this paper presents a bibliometric analysis on the application of a genetic algorithm in logistics and supply chains using data from 1991 to 2024 from the Web of Science database. The authors found a growing trend in the number of publications and citations over the years. This paper serves as an important reference to researchers by highlighting important research areas, such as multi-objective optimization, metaheuristics, sustainability issues in logistics, and machine learning integration. This bibliometric analysis also underlines the importance of Non-Dominated Sorting Genetic Algorithm II (NSGA-II), sustainability, machine learning, and variable neighborhood search in the application of a genetic algorithm in logistics and supply chains in the near future. The integration of a genetic algorithm with machine learning is also a potential research gap to be filled to overcome the limitations of genetic algorithms, such as the long computational time, difficulties in obtaining optimal solutions, and convergence issues for application in logistics and supply chains.

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Section: Applications Of Genetic Algorithms In Logistics and Supply C...mentioning

confidence: 99%

A Bibliometric Analysis of a Genetic Algorithm for Supply Chain Agility

Lam,

Lee

2024

Mathematics

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“…A numerical simulation analysis was performed to obtain the contact stress and rotational traction of the ball hinge structure. Each influencing factor was considered an independent variable and contact stress and rotational traction were considered evaluation indices [43,44] (Table 2). The data samples listed in Table 2 are the contact stress and rotational traction force calculated using the models based on quadratic polynomial regression.…”

Section: Test and Analysis Of The Response Surface Modelmentioning

confidence: 99%

Optimization of Swivel Spherical Hinge Structure Design Based on the Response Surface Method

et al. 2023

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The accurate analysis of key components of a spherical hinge structure directly affects bridge quality and safety during construction. Considering the key components of a spherical joint structure as the research object, a refined calculation model for the spherical joint is established to examine its stress using finite element analysis. The influence of design parameters on the mechanical characteristics of the spherical hinge structure is systematically analyzed. The response surface method (RSM), devised using a Box–Behnken design, is used to optimize the design of the spherical hinge structure parameters. A response surface model is established to derive the scheme of the optimized spherical hinge structure design. Moreover, by comparing the structural contact stress and rotational traction force before and after optimization, the effectiveness and necessity of the spherical hinge structure optimization are verified. The result comparison shows that the maximum contact stress and rotational traction force in the spherical hinge structure after optimization are reduced by 13.86% and 8.42%, respectively, compared with those before optimization. The relative error between the calculated and predicted values is approximately 3%, indicating that the RSM is feasible for optimizing key components of the spherical hinge structure. Its optimization effect is evident. Based on the identified optimal parameters of the spherical hinge structure, a range of recommended design parameters for the key structure of the rotating spherical hinge at different load carrying capacities is established using the interpolation method, which provides a valuable reference for engineering practice.

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“…In practice, these two systems are often combined into one [6]. Passive control is passive control, and its economy and applicability can well meet the actual needs, but there are still many problems in its design [7].…”

Section: Introductionmentioning

confidence: 99%

Parameter optimization design of isolated bridge based on improved genetic algorithm

Huang

2023

Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022)

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It is not uncommon for bridges to be damaged by earthquakes. As an important throat in the transportation network, earthquakes not only cause the loss of bridges themselves, but also cause a series of losses of the transportation network. In the design of bridge seismic isolation, the seismic isolation device is used to isolate the structure from the frequency band where the seismic energy is concentrated and reduce the seismic response of the structure by prolonging the period and increasing the damping. Compared with advanced countries in seismic research, there is a big gap in the research of mechanical model and parameters of seismic isolation devices in China's bridge seismic code. Based on the analysis of the advantages and disadvantages of the finite element sensitivity method and its application limitations, a sequential recurrence method for support optimization is proposed. The results of an example show that the sequential recurrence method has the advantages of strong adaptability and unconditional convergence. On the basis of the sequence recurrence method, the modified sequence recurrence method is further proposed. This method can take into account the influence of the pier inertia force, and is applicable to a variety of support forms. After the genetic algorithm optimization calculation, the difference of the bending moment at the bottom of each pier can be controlled within, which solves the problem of large difference of the bending moment at the bottom of the pier under the longitudinal earthquake of irregular bridges.

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Nonlinear dynamic analysis of the bridge bearing and genetic algorithm–based optimization for seismic mitigation

Cited by 5 publications

References 40 publications

A Bibliometric Analysis of a Genetic Algorithm for Supply Chain Agility

A Bibliometric Analysis of a Genetic Algorithm for Supply Chain Agility

Optimization of Swivel Spherical Hinge Structure Design Based on the Response Surface Method

Parameter optimization design of isolated bridge based on improved genetic algorithm

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