Optimisation of water treatment works performance using genetic algorithms

Roger Swan, Mark Sterling, Jonathan Bridgeman

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)
296 Downloads (Pure)


Verified static and dynamic models of an operational works were used alongside Monte-Carlo conditions and Non-Dominated Sorting Genetic Algorithm II (NGSAII) to optimise operational regimes. Static models were found to be more suitable for whole WTW optimisation modelling and offered the additional advantage of reduced computational burden. Static models were shown to predict solutions of comparable cost when applied to optimisation problems whilst being faster to simulate than dynamic models.
Original languageEnglish
JournalJournal of Hydroinformatics
Early online date9 Jun 2017
Publication statusE-pub ahead of print - 9 Jun 2017


  • Genetic Algorithms
  • Water Treatment Works
  • Optimisation


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