Bayesian network method for decision-making about the social sustainability of infrastructure projects. (1st March 2018)

• Record Type: Journal Article
• Authors: Sierra, Leonardo A.; Yepes, Víctor; García-Segura, Tatiana; Pellicer, Eugenio
• Is Part Of: Journal of cleaner production. Volume 176(2018)
• Page Start: 521
• Page End: 534
• Publication Date: 2018-03-01
• Subjects: Bayesian networks -- Infrastructure -- Multiple criteria -- Optimization algorithm -- Social sustainability; Factory and trade waste -- Management -- Periodicals; Manufactures -- Environmental aspects -- Periodicals; Déchets industriels -- Gestion -- Périodiques; Usines -- Aspect de l'environnement -- Périodiques; 628.5
• DOI: 10.1016/j.jclepro.2017.12.140
• Languages: English
• ISSNs: 0959-6526

Abstract

Abstract: Nowadays, sustainability assessment tends to focus on the biophysical and economic aspects of the built environment. The social aspects are generally overestimated during an infrastructure evaluation. This study proposes a method to optimize infrastructure projects by assessing their social contribution. This proposal takes into account the infrastructure's interactions with the local environment in terms of its potential contribution in the short and long term. The method is structured in three stages: (1) preparation of a decision-making model, (2) formulation of the model, and (3) implementation of the model through optimization of infrastructure projects from the social sustainability viewpoint. The theory of Bayesian reasoning and a harmony search optimization algorithm are used to carry out the research. The paper presents the application to a case study of a set of alternatives for road infrastructure projects in El Salvador. This approach creates a model of participative decision-making. The results show that the method can distinguish socially efficient alternatives from the short and long-term contributions. In addition, the results suggest that some variables are less sensitive to the short and long-term maximization, while others vary their values to improve one objective or the other. The findings are directly applied to a real case. The method can be employed in the infrastructure formulation and prioritization phases and complemented with economic and environmental sustainability assessments. Highlights: Method to optimize social sustainability in infrastructure projects. Highlights social facets of the infrastructure in the short and long term. Bayesian theory and harmony search optimization algorithm are used. Case study application to road infrastructure projects in El Salvador is shown. It allows public agencies to make early decisions on infrastructure projects.