Abstract
The losses in the urban water supply networks have become a growing concern. There are several alternatives for the quantification, detection and monitoring of water losses. However, in general, water companies have budgetary and other constraints that hinder implementation. Therefore, this paper presents a model to aid the selection of a subset of preventive maintenance actions to control water losses while accounting for the water companies’ restrictions. The model combines an additive multi-attribute value analysis by applying the SMARTER method to evaluate alternatives with Integer Linear Programming (ILP). The model shows to be efficient in order to achieve a portfolio of preventive maintenance actions, particularly when the decision maker considers that, there is a compensation for attribute evaluations.
Highlights
Water is a valuable resource, critical to economic development (Horne, 2013)
The SMARTER method requires that the decision‐making model meet the linearity of the one-dimensional utilities for each attribute and the property of the additive independence, in other words, it checks if the values assigned to each alternative on a given attribute are not linked to the values of preferences on other attributes (Valois & Almeida, 2009)
This paper presented a decision model integrating a multi-attribute value method, SMARTER method, with an integer linear programming approach
Summary
Water is a valuable resource, critical to economic development (Horne, 2013). developing countries worldwide face significant challenges in managing increasing demand for urban water because of industrialization, urbanization and the potential impacts of global warming on freshwater supply (Araral & Wang, 2013). The leakage reduction problem as a whole is complex and requires coordinated actions in different areas of the water network management, such as the direct detection and repair of existing leaks, general pipe rehabilitation programs and operational pressure control (Morais & Almeida, 2007). Inadequate maintenance of water supply systems has serious consequences These days when society is faced with severe water shortage scenarios, the search by possible solutions to minimize this problem through a specific strategy for the management of losses is necessary (Morais & de Almeida, 2007). According to Trojan & Morais (2012), problems encountered in the maintenance management of water supply are indicated by the lack of decision support models that give a manager an overview of the system From this statement, this paper aims to analyze preventative actions related to maintenance of the water supply network to control water losses and build a portfolio of the best actions.
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