An exponential chaotic differential evolution algorithm for optimizing bridge maintenance plans

Bridges are one of the fundamental infrastructure assets that are vital for economic growth and public welfare. Over the past few decades, the numbers of deteriorating bridges have drastically escalated raising concerns for serviceable, safe and functional transportation networks. This state of affa...

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Vydané v:Automation in construction Ročník 134; s. 104107
Hlavní autori: Abdelkader, Eslam Mohammed, Moselhi, Osama, Marzouk, Mohamed, Zayed, Tarek
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Amsterdam Elsevier B.V 01.02.2022
Elsevier BV
Predmet:
Algorithms
Bridge maintenance
Bridges
Complex proportional assessment
Criteria
Economic development
Environmental impact
Evolutionary algorithms
Evolutionary computation
Exponential chaotic differential evolution
Infrastructure
Maintenance optimization
Multi-criteria decision making
Multi-objective
Multiple objective analysis
Optimization
Performance enhancement
Physical properties
Project and network levels
Scientific papers
Sine waves
Transportation networks
Bridges
Complex proportional assessment
Exponential chaotic differential evolution
Multi-criteria decision making
Maintenance optimization
Multi-objective
Project and network levels
ISSN:0926-5805, 1872-7891
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Abstract Bridges are one of the fundamental infrastructure assets that are vital for economic growth and public welfare. Over the past few decades, the numbers of deteriorating bridges have drastically escalated raising concerns for serviceable, safe and functional transportation networks. This state of affairs poses a paramount challenge especially when coupled with the need to address social and environmental constraints. Accordingly, this current research paper proposes an automated three-component model for bridge maintenance optimization at both project and network levels. The first component aims at identifying the physical characteristics of the tackled bridge inventory. The second component encompasses designing a multi-objective optimization model to determine the optimal set of maintenance plans through four principal objective functions. These functions comprise maximization of performance condition of bridge elements, minimization of agency and user costs, minimization of duration of traffic disruption and minimization of environmental impact. In the multi-objective optimization model, an exponential chaotic differential evolution (ECDE) algorithm is introduced in an attempt to circumvent the drawbacks of convergence speed and search behavior of classical meta-heuristics. The third component combines criteria importance through inter-criteria correlation (CRITIC), complex proportional assessment (COPRAS) and grey relational analysis (GRA) to select the most optimum maintenance plan for each study period. Comparison results revealed that ECDE-based Sinusoidal algorithm managed to improve the performance diagnostics of classical meta-heuristics by values ranged from 49.2% to 73.1% over the multi-year maintenance plans. The results of benchmark test functions exemplified that ECDE-based Sinusoidal algorithm performed better than genetic and differential evolution algorithms by 114.2% and 79.5%, respectively. The developed integrated model is expected to assist infrastructure managers in executing optimized and sustainable maintenance budget plans within various planning scenarios. •Bibliometric map is presented to derive the key shortcomings of previous research.•A chaotic-based optimization model is formulated for bridge maintenance planning in both project and network levels.•A hybrid multi-criteria decision-making algorithm is designed for prioritizing the Pareto optimum maintenance plans.•A computer aided application is developed using C#.net and Matlab.•The developed multi-objective optimization model is validated using actual case studies and benchmark test functions.
AbstractList Bridges are one of the fundamental infrastructure assets that are vital for economic growth and public welfare. Over the past few decades, the numbers of deteriorating bridges have drastically escalated raising concerns for serviceable, safe and functional transportation networks. This state of affairs poses a paramount challenge especially when coupled with the need to address social and environmental constraints. Accordingly, this current research paper proposes an automated three-component model for bridge maintenance optimization at both project and network levels. The first component aims at identifying the physical characteristics of the tackled bridge inventory. The second component encompasses designing a multi-objective optimization model to determine the optimal set of maintenance plans through four principal objective functions. These functions comprise maximization of performance condition of bridge elements, minimization of agency and user costs, minimization of duration of traffic disruption and minimization of environmental impact. In the multi-objective optimization model, an exponential chaotic differential evolution (ECDE) algorithm is introduced in an attempt to circumvent the drawbacks of convergence speed and search behavior of classical meta-heuristics. The third component combines criteria importance through inter-criteria correlation (CRITIC), complex proportional assessment (COPRAS) and grey relational analysis (GRA) to select the most optimum maintenance plan for each study period. Comparison results revealed that ECDE-based Sinusoidal algorithm managed to improve the performance diagnostics of classical meta-heuristics by values ranged from 49.2% to 73.1% over the multi-year maintenance plans. The results of benchmark test functions exemplified that ECDE-based Sinusoidal algorithm performed better than genetic and differential evolution algorithms by 114.2% and 79.5%, respectively. The developed integrated model is expected to assist infrastructure managers in executing optimized and sustainable maintenance budget plans within various planning scenarios.
Bridges are one of the fundamental infrastructure assets that are vital for economic growth and public welfare. Over the past few decades, the numbers of deteriorating bridges have drastically escalated raising concerns for serviceable, safe and functional transportation networks. This state of affairs poses a paramount challenge especially when coupled with the need to address social and environmental constraints. Accordingly, this current research paper proposes an automated three-component model for bridge maintenance optimization at both project and network levels. The first component aims at identifying the physical characteristics of the tackled bridge inventory. The second component encompasses designing a multi-objective optimization model to determine the optimal set of maintenance plans through four principal objective functions. These functions comprise maximization of performance condition of bridge elements, minimization of agency and user costs, minimization of duration of traffic disruption and minimization of environmental impact. In the multi-objective optimization model, an exponential chaotic differential evolution (ECDE) algorithm is introduced in an attempt to circumvent the drawbacks of convergence speed and search behavior of classical meta-heuristics. The third component combines criteria importance through inter-criteria correlation (CRITIC), complex proportional assessment (COPRAS) and grey relational analysis (GRA) to select the most optimum maintenance plan for each study period. Comparison results revealed that ECDE-based Sinusoidal algorithm managed to improve the performance diagnostics of classical meta-heuristics by values ranged from 49.2% to 73.1% over the multi-year maintenance plans. The results of benchmark test functions exemplified that ECDE-based Sinusoidal algorithm performed better than genetic and differential evolution algorithms by 114.2% and 79.5%, respectively. The developed integrated model is expected to assist infrastructure managers in executing optimized and sustainable maintenance budget plans within various planning scenarios. •Bibliometric map is presented to derive the key shortcomings of previous research.•A chaotic-based optimization model is formulated for bridge maintenance planning in both project and network levels.•A hybrid multi-criteria decision-making algorithm is designed for prioritizing the Pareto optimum maintenance plans.•A computer aided application is developed using C#.net and Matlab.•The developed multi-objective optimization model is validated using actual case studies and benchmark test functions.
ArticleNumber 104107
Author Abdelkader, Eslam Mohammed
Moselhi, Osama
Marzouk, Mohamed
Zayed, Tarek
Author_xml – sequence: 1
  givenname: Eslam Mohammed
  surname: Abdelkader
  fullname: Abdelkader, Eslam Mohammed
  email: eslam_ahmed1990@hotmail.com
  organization: Structural Engineering Department, Faculty of Engineering, Cairo University, Egypt
– sequence: 2
  givenname: Osama
  surname: Moselhi
  fullname: Moselhi, Osama
  organization: Centre for Innovation in Construction and Infrastructure Engineering and Management (CICIEM), Department of Building, Civil, and Environmental Engineering, Concordia University, Montreal, QC, Canada
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  givenname: Mohamed
  surname: Marzouk
  fullname: Marzouk, Mohamed
  organization: Structural Engineering Department, Faculty of Engineering, Cairo University, Egypt
– sequence: 4
  givenname: Tarek
  surname: Zayed
  fullname: Zayed, Tarek
  organization: Department of Building and Real Estate, the Hong Kong Polytechnic University, Hung Hom, Hong Kong
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Keywords Bridges
Complex proportional assessment
Exponential chaotic differential evolution
Multi-criteria decision making
Maintenance optimization
Multi-objective
Project and network levels
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Snippet Bridges are one of the fundamental infrastructure assets that are vital for economic growth and public welfare. Over the past few decades, the numbers of...
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StartPage 104107
SubjectTerms Algorithms
Bridge maintenance
Bridges
Complex proportional assessment
Criteria
Economic development
Environmental impact
Evolutionary algorithms
Evolutionary computation
Exponential chaotic differential evolution
Infrastructure
Maintenance optimization
Multi-criteria decision making
Multi-objective
Multiple objective analysis
Optimization
Performance enhancement
Physical properties
Project and network levels
Scientific papers
Sine waves
Transportation networks
Title An exponential chaotic differential evolution algorithm for optimizing bridge maintenance plans
URI https://dx.doi.org/10.1016/j.autcon.2021.104107
https://www.proquest.com/docview/2627860184
Volume 134
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