Penalty-free multi-objective evolutionary approach to optimization of anytown water distribution network

Calvin Siew, Tiku T. Tanyimboh, Alemtsehay G. Seyoum

Research output: Contribution to journalArticle

11 Citations (Scopus)

Abstract

This paper describes the development and application of a new multi-objective evolutionary optimization approach for the design and upgrading of water distribution systems with multiple pumps and service reservoirs. The optimization model employs a pressure-driven analysis simulator that accounts for the minimum node pressure constraints and conservation of mass and energy. Pump scheduling, tank siting and tank design are integrated seamlessly in the optimization without introducing additional heuristic procedures. The computational solution of the optimization problem is entirely penalty-free, thanks to pressure-driven analysis and the inclusion of explicit criteria for tank depletion and replenishment. The model was applied to the Anytown network that is a benchmark optimization problem. Many new solutions were achieved that are cheaper and offer superior performance compared to previous solutions in the literature. Detailed and extensive simulations of the solutions achieved were carried out. Spatial and temporal variations in water quality were investigated by simulating the chlorine residual and disinfection by-products in addition to water age. The hydraulic requirements were satisfied; efficiency of pumps was consistently high; effective operation of the new and existing tanks was achieved; water quality was improved; and overall computational efficiency was high. The formulation is entirely generic.
LanguageEnglish
Pages3671–3688
Number of pages18
JournalWater Resources Management
Volume30
Issue number11
Early online date3 Jun 2016
DOIs
Publication statusPublished - 1 Sep 2016

Fingerprint

Electric power distribution
pump
Pumps
Water
Water quality
water
water quality
Water distribution systems
Disinfection
Computational efficiency
heuristics
disinfection
Chlorine
Byproducts
simulator
chlorine
Conservation
temporal variation
spatial variation
Simulators

Keywords

  • demand-driven analysis
  • pressure-driven analysis
  • penalty-free constrained multiobjective evolutionary optimization

Cite this

Siew, Calvin ; Tanyimboh, Tiku T. ; Seyoum, Alemtsehay G. / Penalty-free multi-objective evolutionary approach to optimization of anytown water distribution network. In: Water Resources Management. 2016 ; Vol. 30, No. 11. pp. 3671–3688.
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Penalty-free multi-objective evolutionary approach to optimization of anytown water distribution network. / Siew, Calvin; Tanyimboh, Tiku T.; Seyoum, Alemtsehay G.

In: Water Resources Management, Vol. 30, No. 11, 01.09.2016, p. 3671–3688.

Research output: Contribution to journalArticle

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