Li, Junda;
(2023)
Towards Sustainable Highway Pavement Maintenance Management Through Multi-Objective Evolutionary Maintenance Plan Optimisation and Multi-Criteria Decision-Making Based Maintenance Prioritisation.
Doctoral thesis (Ph.D), UCL (University College London).
Abstract
Sustainable highway pavement maintenance management is important for achieving sustainability in the transportation sector. Because the triple bottom lines of sustainability (environmental, economic, and social sustainability) are often contradicting, maximising the sustainability performance of the highway pavements is difficult, especially at the network level. Specifically, highway agencies require a good highway pavement maintenance plan that can guarantee adequate pavement performance during its life cycle, providing users with better service at an acceptable cost while minimising environmental impact. They also require a maintenance priority scheme for pavement sections owing to the uncertainty of constraints in time, budget, manpower, etc., in case they cannot undertake maintenance activities as scheduled in the maintenance plan. This study aimed to develop two decision support models through multi-objective optimisation (MOO) and multi-criteria decision-making (MCDM) to address the two primary problems faced by practitioners in the pavement industry and help them develop more sustainable highway infrastructure. An abductive approach with both qualitative and quantitative methods was employed to address the research problems. First, a synthesised sustainability performance evaluation methodology for the pavement maintenance plan was proposed based on life cycle assessment and life cycle cost analysis, including a list of sustainability performance indicators, which were identified through an extensive literature review. Second, a novel multi-objective evolutionary algorithm was proposed, which is a variant of the multi-objective differential evolution with self-adaptive parameter control and hybrid mutation strategies embedded in its procedures, namely MOSHDE. The proposed MOSHDE was compared with three other state-of-the-art MOO algorithms in a numerical experiment for performance validation. Furthermore, the proposed MOSHDE was applied considering identified sustainability performance indicators and compared to the reactive maintenance policy adopted in current practice in a case study for practical validation. As for pavement maintenance prioritisation, a geographic information system (GIS)-MCDM model was proposed, which considers a set of decision-making factors that were also identified through the literature review. An AHP-based questionnaire survey was conducted with highway experts to determine the weights of identified decision-making factors. With the weighted decision-making factors, the GIS-MCDM model was tested by comparing it with the traditional pavement performance-based prioritisation method in a case study for validation. The thesis contributes to the knowledge related to pavement management, evolutionary computation, and decision-making research by developing two decision support tools that address two primary tasks of sustainable pavement maintenance management, i.e., MOSHDE for pavement maintenance planning and the GIS-MCDM model for pavement maintenance prioritisation. The proposed models outperformed the compared existing methods significantly in all conducted case studies. Therefore, the proposed models have been proved to be practical and effective in dealing with the target issues and helping practitioners develop more sustainable highway pavement infrastructures in pavement management.
| Type: | Thesis (Doctoral) |
|---|---|
| Qualification: | Ph.D |
| Title: | Towards Sustainable Highway Pavement Maintenance Management Through Multi-Objective Evolutionary Maintenance Plan Optimisation and Multi-Criteria Decision-Making Based Maintenance Prioritisation |
| Language: | English |
| Additional information: | Copyright © The Author 2023. Original content in this thesis is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) Licence (https://creativecommons.org/licenses/by-nc/4.0/). Any third-party copyright material present remains the property of its respective owner(s) and is licensed under its existing terms. Access may initially be restricted at the author’s request. |
| Keywords: | Evolutionary algorithm, geographic information system, heuristic algorithm, multi-criteria decision-making, multi-objective optimisation, pavement maintenance, pavement management, sustainability, sustainable development |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10178886 |
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