A distributed constraint multi-agent model for water and reclaimed wastewater allocation in urban areas: Application of a modified ADOPT algorithm

Distributed Constraint Optimization (DCOP)-based approaches, as the distributed version of constraint optimization, provide a framework for coordinated decision making by a team of agents. In this paper, an agent-based DCOP model is developed to allocate water and reclaimed wastewater to demands con...

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Bibliographic Details
Published in:Journal of environmental management Vol. 317; p. 115446
Main Authors: Moradikian, Samaneh, Emami-Skardi, Mohammad Javad, Kerachian, Reza
Format: Journal Article
Language:English
Published: Elsevier Ltd 01.09.2022
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ISSN:0301-4797, 1095-8630, 1095-8630
Online Access:Get full text
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Summary:Distributed Constraint Optimization (DCOP)-based approaches, as the distributed version of constraint optimization, provide a framework for coordinated decision making by a team of agents. In this paper, an agent-based DCOP model is developed to allocate water and reclaimed wastewater to demands considering the conflicting interests of involved stakeholders. One of the well-known DCOP algorithms, ADOPT1, is modified to incorporate an agent responsible for monitoring and conserving water resources. This new algorithm considers the social characteristics of agents and a new form of interaction between agents. For the first time in the literature, a real-world water and reclaimed wastewater allocation problem is formulated as a DCOP and solved using the Modified ADOPT (MADOPT) algorithm. To evaluate the MADOPT algorithm, it is applied to a water and reclaimed wastewater allocation problem in Tehran, Iran. The results illustrate the applicability and efficiency of the proposed methodology in dealing with large-scale multi-agent water resources systems. It is also shown that agents' selfishness and social relationships could affect their water use policies. •A multi-agent model is presented for urban water and treated wastewater management.•A modified version of Asynchronous Distributed Constraint Optimization is proposed.•The algorithm considers a monitoring agent which exists in environmental systems.•The algorithm is applied to a large-scale real-world environmental system.•The results illustrate the applicability and efficiency of the proposed methodology.
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ISSN:0301-4797
1095-8630
1095-8630
DOI:10.1016/j.jenvman.2022.115446