Multi-year maintenance planning framework using multi-attribute utility theory and genetic algorithms

• Main Authors: Zaharah Allah Bukhsh, Irina Stipanovic, Andre G. Doree
• Format: Article
• Language: English
• Published: SpringerOpen 2020-01-01
• Series: European Transport Research Review
• Subjects: Maintenance planning; Multi-objectives; Optimization; Genetic algorithms; Markov decision processes; Multi-attribute
• Online Access: https://doi.org/10.1186/s12544-019-0388-y

Abstract This paper introduces a comprehensive framework for the development of optimal multi-year maintenance plans for a large number of bridges. A maintenance plan is said to be optimal when, within the given budget, a maximum number of bridges can be maintained in the best possible year, achieving maximum performance with minimum socio-economic impact. The framework incorporates heuristic rules, multi-attribute utility theory, discrete Markov chain process, and genetic algorithms to find an optimal balance between limited budgets and performance requirements. The applicability of the proposed framework is illustrated on an extensive case study of highway bridges. The framework enables asset owners to execute various planning scenarios under different budget and performance requirements, where each resulting plan is optimal. The focus of this study has mainly been on highway bridges, however the framework is general and can be applied to any other infrastructure asset type.