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Article Dans Une Revue Procedia Computer Science Année : 2023

Emission-reducing deployment of shared office networks

Résumé

In this paper, we propose 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 comparing 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.
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Dates et versions

hal-04050629 , version 1 (03-05-2023)

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Matthieu Mastio, Sebastian Hörl, Milos Balac, Vincent Loubière. Emission-reducing deployment of shared office networks. Procedia Computer Science, 2023, 220, pp.315-322. ⟨10.1016/j.procs.2023.03.041⟩. ⟨hal-04050629⟩
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