Integrating discrete event simulation and genetic algorithm optimization for bridge maintenance planning

Nili, Mohammad Hosein; Taghaddos, Hosein; Zahraie, Banafsheh

doi:10.1016/j.autcon.2020.103513

Cited by 33 publications

(7 citation statements)

References 42 publications

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“…By combining genetic algorithms and discrete event simulations to identify the optimal maintenance program considering crew constraints, this paper presents a new framework called simulation-based bridge maintenance optimization. This framework optimizes the sequence of restoration activities by considering work space constraints and previous relationships 19 . Han and Frangopol studied bridge networks considering corrosion and assessed their life-cycle connectivity-based maintenance strategy.…”

Section: Literature Reviewmentioning

confidence: 99%

Developing a fuzzy bi-objective programming and MCDM model for bridge maintenance strategy optimization

Shojaei,

Naserabadi,

Taheri Amiri

2024

Sci Rep

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Bridges serve as critical links in road networks, requiring continuous maintenance to ensure proper functionality throughout their lifespan. Given their pivotal role in the urban landscape, connecting various parts of a city, this research presents a multi-objective optimization model for the maintenance and repair of bridges in Babolsar, Iran. The model takes into account budget constraints and aims to minimize the total life cycle and user costs, encompassing traffic delays and vehicle expenses, while maximizing the reliability of the bridge network. Recognizing the inherent complexity of this problem, a multi-objective particle swarm optimization algorithm has been developed for an accurate solution. The study further conducts sensitivity analysis on the objective function concerning the available budget, evaluating key parameters such as hourly costs and the time value of vehicles. The results show that with an increase in the budget level, the number of repairs related to the most costly maintenance has significantly risen. In other words, as the budget expands, the model tends to favor repairs with higher costs because their impact on the bridge’s performance is more substantial.

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Section: Literature Reviewmentioning

confidence: 99%

Developing a fuzzy bi-objective programming and MCDM model for bridge maintenance strategy optimization

Shojaei,

Naserabadi,

Taheri Amiri

2024

Sci Rep

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“…In terms of visual acquisition data, the amount of information required for processing could be reduced if appropriate compression techniques and image quality percentages are adequately determined as done, for example, by Ri et al (2020). By using a BrIM model in combination with Genetic Algorithms (GA) and Discrete Event Simulation (DES), Nili et al (2021) propose a simulation-based framework to optimize bridge intervention (maintenance, rehabilitation and replacement) considering crew limitations. The framework is developed using Microsoft Visual Studio environment, Microsoft Access for the data management and data query, Autodesk Navisworks Manage as the BrIM application software, GA engine for the planning and sequencing modules, and a DES engine of Symphony core service, with a customized.…”

Section: Bridge Digital Twinsmentioning

confidence: 99%

Bridge management through digital twin-based anomaly detection systems: A systematic review

Rios

Plevris

Nogal

2023

Front. Built Environ.

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Bridge infrastructure has great economic, social, and cultural value. Nevertheless, many of the infrastructural assets are in poor conservation condition as has been recently evidenced by the collapse of several bridges worldwide. The objective of this systematic review is to collect and synthesize state-of-the-art knowledge and information about how bridge information modeling, finite element modeling, and bridge health monitoring are combined and used in the creation of digital twins (DT) of bridges, and how these models could generate damage scenarios to be used by anomaly detection algorithms for damage detection on bridges, especially in bridges with cultural heritage value. A total of 76 relevant studies from 2017 up to 2022 have been taken into account in this review. The synthesis results show a consensus toward the future adoption of DT for bridge design, management, and operation among the scientific community and bridge practitioners. The main gaps identified are related to the lack of software interoperability, the required improvement of the performance of anomaly-detection algorithms, and the approach definition to be adopted for the integration of DT at the macro scale. Other potential developments are related to the implementation of Industry 5.0 concepts and ideas within DT frameworks.

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“…It is observed that the proposed approach demonstrated a better performance than the traditional methods in terms of assuring higher reliability in meeting the planned project completion time. Nili et al 40 presented a new optimization framework by integrating DES with a GA to obtain the optimal sequence of repairment activities in maintenance projects to minimize cost. The proposed simulation-based optimization method was implemented for a real case study, and the findings showed the capability and accuracy of the proposed method in optimizing the maintenance plan and estimating the costs.…”

Section: Introductionmentioning

confidence: 99%

Trade-off between time and cost in project planning: a simulation-based optimization approach

Senses,

Kumral

2023

SIMULATION

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Mine development or construction projects should be carefully scheduled to meet the project objectives in terms of duration, budget, and scope since they include many highly time- and cost-sensitive activities. The inherent complexity in mining operations, coupled with material, equipment, and resource availabilities, commodity price cyclicality, and market trend uncertainties, can lead to a high risk to the project, resulting in schedule and cost overruns. Therefore, these projects must be planned and controlled efficiently to ensure that the required capital investment does not exceed the project budget and the project deadline is met. This paper proposes a simulation-based model to optimize the trade-off between time and cost of project planning problems under uncertainty. In doing so, equally probable realizations are generated considering different project duration crashing scenarios to quantify the impact of uncertainty on the total project cost and project completion time, and risks are assessed. A numerical example is provided to show the performance of the proposed approach through an underground mine development project. Statistical analysis of the results obtained from the developed simulation model identifies the risk of project completion time, the criticality of activities, and bottleneck activities of the project. In addition, the time–cost trade-off is achieved under the project deadline and budget constraints by implementing 20,736 different crashing scenarios. Finally, the results obtained from the developed formulation are compared with those obtained from the linear programming solution. The proposed approach has a strong potential to add value to project management of mining projects.

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Integrating discrete event simulation and genetic algorithm optimization for bridge maintenance planning

Cited by 33 publications

References 42 publications

Developing a fuzzy bi-objective programming and MCDM model for bridge maintenance strategy optimization

Developing a fuzzy bi-objective programming and MCDM model for bridge maintenance strategy optimization

Bridge management through digital twin-based anomaly detection systems: A systematic review

Trade-off between time and cost in project planning: a simulation-based optimization approach

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