An integrated optimisation platform for sustainable resource and infrastructure planning
File(s)1-s2.0-S1364815217301391-main.pdf (7.3 MB)
Published version
Author(s)
Triantafyllidis, CP
Koppelaar, RHEM
Wang, X
van Dam, KH
Shah, N
Type
Journal Article
Abstract
It is crucial for sustainable planning to consider broad environmental and social dimensions and systemic implications of new infrastructure to build more resilient societies, reduce poverty, improve human well-being, mitigate climate change and address other global change processes. This article presents resilience.io, 2 a platform to evaluate new infrastructure projects by assessing their design and effectiveness in meeting growing resource demands, simulated using Agent-Based Modelling due to socio-economic population changes. We then use Mixed-Integer Linear Programming to optimise a multi-objective function to find cost-optimal solutions, inclusive of environmental metrics such as greenhouse gas emissions. The solutions in space and time provide planning guidance for conventional and novel technology selection, changes in network topology, system costs, and can incorporate any material, waste, energy, labour or emissions flow. As an application, a use case is provided for the Water, Sanitation and Hygiene (WASH) sector for a four million people city-region in Ghana.
Date Issued
2018-01-05
Date Acceptance
2017-11-16
Citation
Environmental Modelling and Software, 2018, 101, pp.146-168
ISSN
1364-8152
Publisher
Elsevier
Start Page
146
End Page
168
Journal / Book Title
Environmental Modelling and Software
Volume
101
Copyright Statement
© 2017 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND
license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Sponsor
United Nations Office for Project Services
Grant Number
CA/FCA/TEST/2014
Subjects
MD Multidisciplinary
Environmental Engineering
Publication Status
Published