Embedding linear programming in multi objective genetic algorithms for reducing the size of the search space with application to leakage minimization in water distribution networks

Creaco, Enrico; Pezzinga, Giuseppe

doi:10.1016/j.envsoft.2014.10.013

Cited by 60 publications

(49 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…In the present section, first the LP used in both SA [15] and GA [17,18] for the optimization of control valve settings is described (Section 2.1). Sections 2.2 and 2.3 are dedicated to describing the different approaches used in SA and GA, respectively, to tackle optimal valve locations.…”

Section: Methodsmentioning

confidence: 99%

“…Whereas all the algorithms cited above are based on the single-objective approach, other algorithms [15][16][17][18] were conceived using the multi-objective approach, to construct Pareto fronts of optimal solutions in the tradeoff between number of control valves, as a surrogate for the installation cost, and daily leakage. Pezzinga and Gueli [15] proposed, for optimal valve location, a fully deterministic procedure, based on the sequential addition (SA) of beneficial valves up to a maximum number of valves installable in the WDN has been fixed.…”

Section: Introductionmentioning

confidence: 99%

“…The lack of this kind of comparison in the scientific literature has motivated the present work. The algorithms of Pezzinga and Gueli [15] and of Creaco and Pezzinga [17,18] were chosen as representative for the comparison. The former was chosen because of its fully deterministic approach, which confers significant computational lightness on the methodology.…”

Section: Introductionmentioning

confidence: 99%

“…Nicolini and Zovatto [16] used a multi-objective GA to optimize both valve locations and control settings. Creaco and Pezzinga [17,18] used a GA to search for the optimal valve locations, and LP to optimize the control valve settings for each solution proposed by the GA.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Comparison of Algorithms for the Optimal Location of Control Valves for Leakage Reduction in WDNs

Creaco

Pezzinga

2018

Water

View full text Add to dashboard Cite

Abstract:The paper presents the comparison of two different algorithms for the optimal location of control valves for leakage reduction in water distribution networks (WDNs). The former is based on the sequential addition (SA) of control valves. At the generic step N val of SA, the search for the optimal combination of N val valves is carried out, while containing the optimal combination of N val − 1 valves found at the previous step. Therefore, only one new valve location is searched for at each step of SA, among all the remaining available locations. The latter algorithm consists of a multi-objective genetic algorithm (GA), in which valve locations are encoded inside individual genes. For the sake of consistency, the same embedded algorithm, based on iterated linear programming (LP), was used inside SA and GA, to search for the optimal valve settings at various time slots in the day. The results of applications to two WDNs show that SA and GA yield identical results for small values of N val . When this number grows, the limitations of SA, related to its reduced exploration of the research space, emerge. In fact, for higher values of N val , SA tends to produce less beneficial valve locations in terms of leakage abatement. However, the smaller computation time of SA may make this algorithm preferable in the case of large WDNs, for which the application of GA would be overly burdensome.

show abstract

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Comparison of Algorithms for the Optimal Location of Control Valves for Leakage Reduction in WDNs

Creaco

Pezzinga

2018

Water

View full text Add to dashboard Cite

show abstract

“…Similar to Creaco and Pezzinga (2015), Li et al (2015) also tackle the issue of search space size reduction by means of a hybrid EA-linear programming approach. However, their approach is applicable to the optimisation of multi-reservoir systems with heterogeneous hydropower units and involves the use of EAs for multi-reservoir optimisation as part of an outer loop and the use of linear programming for optimal unit scheduling as part of an inner loop.…”

Section: Hr Maier Z Kapelan J Kasprzyk Ls Matottmentioning

confidence: 99%

Thematic issue on Evolutionary Algorithms in Water Resources

Maier¹,

Kapelan²,

Kasprzyk³

et al. 2015

Environmental Modelling & Software

View full text Add to dashboard Cite

On the choice of the demand and hydraulic modeling approach to WDN real‐time simulation

Creaco

Pezzinga

Savić

2017

Water Resources Research

View full text Add to dashboard Cite

This paper aims to analyze two demand modeling approaches, i.e., top‐down deterministic (TDA) and bottom‐up stochastic (BUA), with particular reference to their impact on the hydraulic modeling of water distribution networks (WDNs). In the applications, the hydraulic modeling is carried out through the extended period simulation (EPS) and unsteady flow modeling (UFM). Taking as benchmark the modeling conditions that are closest to the WDN's real operation (UFM + BUA), the analysis showed that the traditional use of EPS + TDA produces large pressure head and water discharge errors, which can be attenuated only when large temporal steps (up to 1 h in the case study) are used inside EPS. The use of EPS + BUA always yields better results. Indeed, EPS + BUA already gives a good approximation of the WDN's real operation when intermediate temporal steps (larger than 2 min in the case study) are used for the simulation. The trade‐off between consistency of results and computational burden makes EPS + BUA the most suitable tool for real‐time WDN simulation, while benefitting from data acquired through smart meters for the parameterization of demand generation models.

show abstract

Embedding linear programming in multi objective genetic algorithms for reducing the size of the search space with application to leakage minimization in water distribution networks

Cited by 60 publications

References 26 publications

Comparison of Algorithms for the Optimal Location of Control Valves for Leakage Reduction in WDNs

Comparison of Algorithms for the Optimal Location of Control Valves for Leakage Reduction in WDNs

Thematic issue on Evolutionary Algorithms in Water Resources

On the choice of the demand and hydraulic modeling approach to WDN real‐time simulation

Contact Info

Product

Resources

About