An Integrated Multi-Objectives Optimization Approach on Modelling Pavement Maintenance Strategies for Pavement Sustainability

Ji, Ankang; Xue, Xiaolong; Wang, Yuna; Luo, Xiaowei; Zhang, Minggong

doi:10.3846/jcem.2020.13751

Cited by 9 publications

(3 citation statements)

References 51 publications

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“…This is achieved through the application of Markov chain and a particle swarm optimization algorithm that aims to consider the predicted pavement condition and optimize maintenance strategies during operation when applied in the maintenance management of a road pavement section. The results obtained, compared with the linear program, show that the integrated approach is effective and reliable in determining the maintenance strategy that can be employed to promote pavement sustainability [48].…”

Section: Consultation and Analysis Of The Literaturementioning

confidence: 98%

Optimization tools applied to physical asset maintenance management: state of the art

Pentón

Morales

Llanes

et al. 2021

DYNA

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This article presents the state of the art of the application of optimization tools such as Genetic Algorithms, Simulation, Neural Networks, Markov Chains and Bayesian Networks in the physical asset maintenance management. The bibliographic references used were extracted from a detailed search that allowed the selection of the empirical studies presented, in the time horizon from 2010 to 2021, through databases, research platforms and online libraries. The analysis of the identified case studies is carried out, taking into account the variables involved in the study, the optimization tool used, and the result obtained in the analysis of the physical asset maintenance management. The benefits of the application of optimization tools are identified and it is confirmed that maintenance costs and intervention times are present variables, which contribute to the improvement of reliability and maintenance management.

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Section: Consultation and Analysis Of The Literaturementioning

confidence: 98%

Optimization tools applied to physical asset maintenance management: state of the art

Pentón

Morales

Llanes

et al. 2021

DYNA

View full text Add to dashboard Cite

show abstract

“…Making decisions regarding the maintenance of buildings requires taking into consideration many factors. Therefore, this problem is often solved using MCDM (Multiple Criteria Decision Making) methods [10][11][12][13][14][15][16][17][18]. Peach and Visser [19] analyze the problem of including human factors in maintenance.…”

Section: Literature Summarymentioning

confidence: 99%

Analysis of the Impact of Input Data on the Planned Costs of Building Maintenance

Plebankiewicz

Gracki

2021

Sustainability

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The aim of the article is to analyze the method of determining the maintenance costs of buildings based on the method proposed in Polish legal regulations. The analysis of the sensitivity of the method shows that the assumed number of product use cycles during the calculation period has the greatest impact, while the adopted warranty period has the lowest impact. A multi-functional building combining housing, office, service and commercial was analyzed in order to obtain a broader picture of the model’s operation. The results of the analyses allow us to conclude that despite the higher price of materials, the most durable solutions, which are the most expensive to purchase, turn out to be the most advantageous in the entire life cycle of the building. The method proposed in Polish law regulations has certain limitations. In order to level them, it was proposed to extend the method by using NPV (Net Present Value) for calculations and extending the life cycle of the building to 80 years.

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“…Real-world optimization problems pervade almost every scientific domain, and many engineering challenges can readily be transformed into optimization problems (Podolski & Sroka, 2019;Ji et al, 2020;Es-Haghi et al, 2022). These problems pose significant challenges, often involving nonlinearity, multiple objectives, discontinuities, high dimensions, uncertainties, and non-convex regions (Cheng & Cao, 2016).…”

Section: Introductionmentioning

confidence: 99%

Integrating Enhanced Optimization With Finite Element Analysis for Designing Steel Structure Weight Under Multiple Constraints

Truong,

Chou

2023

Journal of Civil Engineering and Management

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Real-world optimization problems are ubiquitous across scientific domains, and many engineering challenges can be reimagined as optimization problems with relative ease. Consequently, researchers have focused on developing optimizers to tackle these challenges. The Snake Optimizer (SO) is an effective tool for solving complex optimization problems, drawing inspiration from snake patterns. However, the original SO requires the specification of six specific parameters to operate efficiently. In response to this, enhanced snake optimizers, namely ESO1 and ESO2, were developed in this study. In contrast to the original SO, ESO1 and ESO2 rely on a single set of parameters determined through sensitivity analysis when solving mathematical functions. This streamlined approach simplifies the application of ESOs for users dealing with optimization problems. ESO1 employs a logistic map to initialize populations, while ESO2 further refines ESO1 by integrating a Lévy flight to simulate snake movements during food searches. These enhanced optimizers were compared against the standard SO and 12 other established optimization methods to assess their performance. ESO1 significantly outperforms other algorithms in 15, 16, 13, 15, 21, 16, 24, 16, 19, 18, 13, 15, and 22 out of 24 mathematical functions. Similarly, ESO2 outperforms them in 16, 17, 18, 22, 23, 23, 24, 20, 19, 20, 17, 22, and 23 functions. Moreover, ESO1 and ESO2 were applied to solve complex structural optimization problems, where they outperformed existing methods. Notably, ESO2 generated solutions that were, on average, 1.16%, 0.70%, 2.34%, 3.68%, and 6.71% lighter than those produced by SO, and 0.79%, 0.54%, 1.28%, 1.70%, and 1.60% lighter than those of ESO1 for respective problems. This study pioneers the mathematical evaluation of ESOs and their integration with the finite element method for structural weight design optimization, establishing ESO2 as an effective tool for solving engineering problems.

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An Integrated Multi-Objectives Optimization Approach on Modelling Pavement Maintenance Strategies for Pavement Sustainability

Cited by 9 publications

References 51 publications

Optimization tools applied to physical asset maintenance management: state of the art

Optimization tools applied to physical asset maintenance management: state of the art

Analysis of the Impact of Input Data on the Planned Costs of Building Maintenance

Integrating Enhanced Optimization With Finite Element Analysis for Designing Steel Structure Weight Under Multiple Constraints

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