Repositorio
Institucional

Pellicer, Eugenio

Sierra, Leonardo A.#Yepes, Victor#Garcia-Segura, Tatiana

Bayesian network method for decision-making about the social sustainability of infrastructure projects

ELSEVIER SCI LTD

JOURNAL OF CLEANER PRODUCTION

en

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. (C) 2017 Elsevier Ltd. All rights reserved.

Artículo original

This research was funded by the Government of Chile under the Doctoral Fellowship Abroad Program (grant CONICYT-2015/72160059) and the Spanish Ministry of Economy and Competitiveness along with FEDER funding (project BIA2014-56574-R). The authors are grateful to both the United Nations Development Programme and the Ministry of Public Works, Transportation, Housing and Urban Development of El Salvador for their participation in the implementation of the proposed method (Project 00074250).

Esta investigación fue financiada por el Gobierno de Chile en el marco del Programa de Becas de Doctorado en el Extranjero (beca CONICYT-2015/72160059) y el Ministerio de Economía y Competitividad de España, junto con fondos FEDER (proyecto BIA2014-56574-R). Los autores agradecen al Programa de las Naciones Unidas para el Desarrollo (PNUD) y al Ministerio de Obras Públicas, Transporte, Vivienda y Urbanismo de El Salvador su participación en la implementación del método propuesto (Proyecto 00074250).

10.1016/j.jclepro.2017.12.140

pdf

Bayesian networks# Infrastructure# Multiple criteria# Optimization algorithm# Social sustainability

http://dx.doi.org/10.1016/j.jclepro.2017.12.140

Green & Sustainable Science & Technology# Engineering, Environmental# Environmental Sciences

redes bayesianas# Infraestructura# Múltiples criterios# Algoritmo de optimización# Sostenibilidad social

Ingeniería de Transporte

Ciencias Sociales Interdisciplinarias

Ingeniería Civil

version publicada

hibrida

verde

metadata

metadata

WOS:000423648000048

Bayesian network method for decision-making about the social sustainability of infrastructure projects

hdl.handle.net/10251/141964

Artículo original

ELSEVIER SCI LTD

JOURNAL OF CLEANER PRODUCTION

Ciencia y tecnología verdes y sostenibles# Ingeniería Ambiental# Ciencias Ambientales

0959-6526

en

ANID 72160059#MINECO FEDER BIA2014-56574-R#PNUD/MOP 00074250

ANID CONICYT 2015 72160059

MINECO

FEDER BIA2014-56574-R

Ministry of Public Works, Transportation, Housing and Urban Development of El Salvador 00074250

United Nations Development Programme

This research was funded by the Government of Chile under the Doctoral Fellowship Abroad Program (grant CONICYT-2015/72160059) and the Spanish Ministry of Economy and Competitiveness along with FEDER funding (project BIA2014-56574-R). The authors are grateful to both the United Nations Development Programme and the Ministry of Public Works, Transportation, Housing and Urban Development of El Salvador for their participation in the implementation of the proposed method (Project 00074250).

pdf

5817

5846