Yan Zhang, L. Chouinard, G. Power, D. Conciatori, K. Sasai, Abdoul S. Bah
{"title":"Multi-objective optimization for the sustainability of infrastructure projects under the influence of climate change","authors":"Yan Zhang, L. Chouinard, G. Power, D. Conciatori, K. Sasai, Abdoul S. Bah","doi":"10.1080/23789689.2023.2171197","DOIUrl":null,"url":null,"abstract":"ABSTRACT Infrastructure asset management is concerned with the efficient and sustainable utilization of resources. There are numerous sources of uncertainties associated with the physical state of the infrastructure, climate change, and the economy. Thus, the most appropriate decision-making process to select maintenance and replacement strategies that are sustainable, economical, and safe should also be well informed in terms of risks. The decision process is formulated as a multi-objective optimization problem and exemplified the case for targeted performance levels and total costs, and solved using both Multi-Objective Particle Swarm Optimization (MOPSO) and a Non-dominated Sorting Genetic Algorithm II (NSGA-II). The results indicate that annual budget constraints have a significant effect on the Pareto front and the schedule associated with individual solutions. The proposed approach provides a useful and flexible decision-analysis tool for managers by allowing for multiple objective optimization in scheduling future interventions towards the sustainability of infrastructure.","PeriodicalId":45395,"journal":{"name":"Sustainable and Resilient Infrastructure","volume":null,"pages":null},"PeriodicalIF":2.7000,"publicationDate":"2023-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Sustainable and Resilient Infrastructure","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/23789689.2023.2171197","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, CIVIL","Score":null,"Total":0}
引用次数: 0
Abstract
ABSTRACT Infrastructure asset management is concerned with the efficient and sustainable utilization of resources. There are numerous sources of uncertainties associated with the physical state of the infrastructure, climate change, and the economy. Thus, the most appropriate decision-making process to select maintenance and replacement strategies that are sustainable, economical, and safe should also be well informed in terms of risks. The decision process is formulated as a multi-objective optimization problem and exemplified the case for targeted performance levels and total costs, and solved using both Multi-Objective Particle Swarm Optimization (MOPSO) and a Non-dominated Sorting Genetic Algorithm II (NSGA-II). The results indicate that annual budget constraints have a significant effect on the Pareto front and the schedule associated with individual solutions. The proposed approach provides a useful and flexible decision-analysis tool for managers by allowing for multiple objective optimization in scheduling future interventions towards the sustainability of infrastructure.
期刊介绍:
Sustainable and Resilient Infrastructure is an interdisciplinary journal that focuses on the sustainable development of resilient communities.
Sustainability is defined in relation to the ability of infrastructure to address the needs of the present without sacrificing the ability of future generations to meet their needs. Resilience is considered in relation to both natural hazards (like earthquakes, tsunami, hurricanes, cyclones, tornado, flooding and drought) and anthropogenic hazards (like human errors and malevolent attacks.) Resilience is taken to depend both on the performance of the built and modified natural environment and on the contextual characteristics of social, economic and political institutions. Sustainability and resilience are considered both for physical and non-physical infrastructure.