Sewer Network Multi-objective Optimization using Genetic Algorithms


  • Iulian Vasiliev Dunărea de Jos University of Galati
  • Laurențiu Luca Dunărea de Jos University of Galati
  • Marian Barbu Dunărea de Jos University of Galati
  • Ramon Vilanova Autonomous University of Barcelona
  • Sergiu Caraman Dunărea de Jos University of Galati



wastewater, sewer network, multi-objective optimization, controlled elitist genetic algorithm


This paper focuses on the multi-objective optimization of a sewer network that serves a medium-sized Romanian city, with a population of 250,000 residents. The sewer network is modeled using BSMSewer software package. The obtained results are based on numerical simulations with the optimization algorithm considering two performance criteria: the volume of overflow and the quality of the overflowed wastewater. For optimization, two approaches that use a controlled elitist genetic algorithm were employed: a multi-objective optimization and a two-steps multi-objective optimization. Results analysis involved comparing them with a scenario where each performance criterion was separately minimized. Additionally, a comparison was made to the situation where the sewer network operated without a control system, meaning the valves were fully open and the pumps were running at maximum capacity.


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How to Cite

“Sewer Network Multi-objective Optimization using Genetic Algorithms”, Syst. Theor. Control Comput. J., vol. 3, no. 1, pp. 45–50, Jun. 2023, doi: 10.52846/stccj.2023.3.1.49.