River water quality management model using genetic algorithm

Aras E., Togan V., BERKUN M.

ENVIRONMENTAL FLUID MECHANICS, vol.7, no.5, pp.439-450, 2007 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 7 Issue: 5
  • Publication Date: 2007
  • Doi Number: 10.1007/s10652-007-9037-4
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.439-450
  • Keywords: self purification, genetic algorithm, dissolved oxygen, treatment cost optimization, river pollution, PARAMETERS, BOD, OPTIMIZATION, STREAMS
  • Karadeniz Technical University Affiliated: Yes


Conventional mathematical programming methods, such as linear programming, non linear programming, dynamic programming and integer programming have been used to solve the cost optimization problem for regional wastewater treatment systems. In this study, a river water quality management model was developed through the integration of a genetic algorithm (GA). This model was applied to a river system contaminated by three determined discharge sources to achieve the water quality goals and wastewater treatment cost optimization in the river basin. The genetic algorithm solution, described the treatment plant efficiency, such that the cost of wastewater treatment for the entire river basin is minimized while the water quality constraints in each reach are satisfied. This study showed that genetic algorithm can be applied for river water quality modeling studies as an alternative to the present methods.