Optimized phased planning for dynamic rehabilitation of integrated municipal infrastructure

Author:

Minaei Amin12ORCID,Abusamra Soliman34,Hajibabaei Mohsen2ORCID,Savic Dragan56ORCID,Zecchin Aaron C.7,Creaco Enrico8ORCID,Sitzenfrei Robert2ORCID

Affiliation:

1. a Austrian Academy of Sciences, 1010 Vienna, Austria

2. b Unit of Environmental Engineering, Department of Infrastructure Engineering, University of Innsbruck, Technikerstrasse 13, 6020 Innsbruck, Austria

3. c Concordia University, Montreal, QC, Canada

4. d VIA HFR-TGF, Montréal, Québec, Canada

5. e KWR-Water Research Institute, 3430 PE Nieuwegein, The Netherlands

6. f Centre for Water Systems, University of Exeter, North Park Road, Exeter EX4 4QF, UK

7. g School of Architecture and Civil Engineering, The University of Adelaide, Adelaide 5005, South Australia

8. h Dipartimento di Ingegneria Civile e Architettura, Università degli Studi di Pavia, Via Ferrata 3, 27100 Pavia, Italy

Abstract

ABSTRACT Phased planning for municipal infrastructure is based on the time-dependent status of multiple networks, which is in contrast to the traditional approach, where one-phase construction and a single status are considered for planning system activities. This study integrates and optimizes the corridor-wise intervention planning of water, sewer, and road networks where the number of equally long phases and intervention decisions are among the decision variables showing the extent to which phase number optimization can impact the cost and coordination of the interventions in interdependent systems. Optimizing the phase number for municipal infrastructure optimization within an evolutionary algorithm is a challenging task due to the evolutionary recombination between numerous planning solutions with different decision variable lengths. A multi-phase design and construction approach is developed for the rehabilitation of the system in a real case study in Montreal, Canada. The study involves 20 corridors in which a street section is co-located with water and sewer pipes. A metaheuristic single-objective optimization engine is employed to minimize the total net present value of intervention plan costs for the whole integrated system. The results show that phased optimization could bring about a 25% cost saving for the rehabilitation master plan and coordinated multi-systems intervention activities.

Funder

H2020 European Research Council

Österreichischen Akademie der Wissenschaften

Österreichische Agentur für Internationale Mobilität und Kooperation in Bildung, Wissenschaft und Forschung

Austrian Science Fund

Publisher

IWA Publishing

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