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Emission-reducing deployment of shared office networks.

Authors :
Mastio, Matthieu
Hörl, Sebastian
Balac, Milos
Loubière, Vincent
Source :
Procedia Computer Science; 2023, Vol. 220, p315-322, 8p
Publication Year :
2023

Abstract

In this paper, we propose a generic method based on publicly available data to design a master plan optimizing the number of coworking spaces to deploy in a given area, as well as their placements across the territory, with the goal of reducing the GHC emissions linked to car commuting. As a first step, we collect and preprocess population data to convert them into an exploitable form. Then we design a decision model that describes when a person would choose to work in a shared office, and which transport mode they would use. We finally perform an optimization to maximize the gains in terms of traveled distance using a linear solver and heuristic methods, and compare their respective effectiveness. The results are encouraging, since they show that using an optimized network computed with our method, we could reduce the total car commuting distance by 23%, which represents a reduction in carbon emissions of hundreds of tons per day at the scale of the studied use case region around Toulouse. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
18770509
Volume :
220
Database :
Supplemental Index
Journal :
Procedia Computer Science
Publication Type :
Academic Journal
Accession number :
163145277
Full Text :
https://doi.org/10.1016/j.procs.2023.03.041