A novel evolutionary meta-heuristic for the multi-objective optimization of real-world water distribution networks

2006 ◽  
Vol 38 (3) ◽  
pp. 319-333 ◽  
Author(s):  
Edward Keedwell ◽  
Soon-Thiam Khu
2021 ◽  
Vol 218 ◽  
pp. 18-31
Author(s):  
Douglas F. Surco ◽  
Diogo H. Macowski ◽  
Flávia A.R. Cardoso ◽  
Thelma P.B. Vecchi ◽  
Mauro A.S.S. Ravagnani

2019 ◽  
Vol 22 (2) ◽  
pp. 402-422 ◽  
Author(s):  
Matthew B. Johns ◽  
Edward Keedwell ◽  
Dragan Savic

Abstract Water system design problems are complex and difficult to optimise. It has been demonstrated that involving engineering expertise is required to tackle real-world problems. This paper presents two engineering inspired hybrid evolutionary algorithms (EAs) for the multi-objective design of water distribution networks. The heuristics are developed from traditional design approaches of practicing engineers and integrated into the mutation operator of a multi-objective EA. The first engineering inspired heuristic is designed to identify hydraulic bottlenecks within the network and eliminate them with a view to speeding up the algorithm's search to the feasible solution space. The second heuristic is based on the notion that pipe diameters smoothly transition from large, at the source, to small at the extremities of the network. The performance of the engineering inspired hybrid EAs is compared with Non-Dominated Sorting Genetic Algorithm II and assessed on three networks of varying complexity, two benchmarks and one real-world network. The experiments presented in this paper demonstrate that the incorporation of engineering expertise can improve EA performance, often producing superior solutions both in terms of mathematical optimality and also engineering feasibility.


2020 ◽  
Vol 20 (7) ◽  
pp. 2630-2647
Author(s):  
Mohammad Solgi ◽  
Omid Bozorg-Haddad ◽  
Hugo A. Loáiciga

Abstract Intermittent operation of water distribution networks (WDNs) is an undesirable yet inevitable strategy under some circumstances such as droughts, development, electricity blackouts, and water pollution, mostly in developing countries. Intermittent utilization of WDNs poses several disadvantages encompassing water quality degradation, deterioration of the water-distribution system, and extra operational and maintenance costs due to frequently interrupted supply, unfair water distribution among consumers, and reduction of system serviceability. This paper proposes a multi-objective optimization model to address the negative consequences of intermittent water shortages. The model is intended to maximize the quantitative and qualitative reliability and the fairness in water supply, and to minimize the frequency of supply interruption. The developed model also considers pragmatic limitations, water quality, water pressure, and supply reservoir's constraints to plan the operation of intermittent water distribution systems under water shortage. The model's efficiency is tested with a WDN in Iran and compared with a standard operation policy (SOP) for water distribution. According to the evaluated efficiency criteria concerning reliability, resiliency, and vulnerability of water quality and quantity of water supply, the developed model is superior to the SOP rule and improves the performance of the network under intermittent operation. In addition, the results demonstrate there is a tradeoff between the uniformity of water distribution and the frequency of supply interruption that shows operators’ and customers’ conflicting priorities.


Water ◽  
2019 ◽  
Vol 11 (10) ◽  
pp. 2018
Author(s):  
Jimmy H. Gutiérrez-Bahamondes ◽  
Yamisleydi Salgueiro ◽  
Sergio A. Silva-Rubio ◽  
Marco A. Alsina ◽  
Daniel Mora-Meliá ◽  
...  

Efficient design and management of water distribution networks is critical for conservation of water resources and minimization of both energy requirements and maintenance costs. Several computational routines have been proposed for the optimization of operational parameters that govern such networks. In particular, multi-objective evolutionary algorithms have proven to be useful both properly describing a network and optimizing its performance. Despite these computational advances, practical implementation of multi-objective optimization algorithms for water networks is an abstruse subject for researchers and engineers, particularly since efficient coupling between multi-objective algorithms and the hydraulic network model is required. Further, even if the coupling is successfully implemented, selecting the proper set of multi-objective algorithms for a given network, and addressing the quality of the obtained results (i.e., the approximate Pareto frontier) introduces additional complexities that further hinder the practical application of these algorithms. Here, we present an open-source project that couples the EPANET hydraulic network model with the jMetal framework for multi-objective optimization, allowing flexible implementation and comparison of different metaheuristic optimization algorithms through statistical quality assessment. Advantages of this project are discussed by comparing the performance of different multi-objective algorithms (i.e., NSGA-II, SPEA2, SMPSO) on case study water pump networks available in the literature.


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