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Journal of Optimization
Volume 2017 (2017), Article ID 4373952, 13 pages
https://doi.org/10.1155/2017/4373952
Research Article

Water Network Design Using a Multiobjective Real Options Framework

1Marine and Environmental Sciences Centre (MARE), Department of Civil Engineering, University of Coimbra, Coimbra, Portugal
2Centre for Water Systems, School of Engineering, Computing and Mathematics, University of Exeter, Exeter, UK
3Department of Civil Engineering and Architecture, Technical University of Bari, Bari, Italy

Correspondence should be addressed to João Marques

Received 13 October 2016; Accepted 4 January 2017; Published 31 January 2017

Academic Editor: Hamed Fazlollahtabar

Copyright © 2017 João Marques et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Water distribution networks (WDNs) are an essential element of urban infrastructure. To achieve a good level of performance, the traditional design of WDNs based on expected future conditions should be replaced by a flexible design, using real options (ROs), that accounts for uncertainty by taking a broader view of possible future options. This work proposes a multiobjective ROs framework that sets out to reduce costs, minimize hydraulic pressure deficiency, and a third objective for minimizing carbon emissions. A multiobjective simulated annealing algorithm is used to identify the Pareto-optimal solutions, thus enabling a trade-off analysis between solutions. These trade-offs show that a low pressure deficit solution is achieved by increasing investment at a much faster rate after a certain pressure deficit threshold (60 m). Also, the pressure deficits can only be reduced by increasing carbon emissions. Finally, this work also emphasizes the importance of including carbon emissions as a specific objective by comparing the results of the proposed model and another one that did not cover the environmental objective. The results show that it is possible to reduce CO2 for the same level of capital expenditure or the same level of network pressure deficits if carbon emissions are minimized in the optimization process.