Development of software for optimal design and management of storm sewer systems (1998-2000)

Funding body: Teaching Company Directorate, DTI and Ewan Optimal Solutions Ltd

The privatisation-led drive in the UK water industry towards increasing efficiency and effectiveness has led to the water companies requiring the optimal performance from their assets. The regulator has also placed particular emphasis on improving combined sewer overflow (CSO) discharges during the AMP3 Period. These market pressures have led to the introduction of novel computing techniques that improve the decision making process. One such technique is the genetic algorithm (GA), whose potential to optimise urban drainage systems was identified by Rauch and Harremos (1998). Genetic algorithms are general artificial evolution search methods based on natural selection and mechanisms of population genetics. They emulate nature's very effective optimisation techniques of evolution, which are based on preferential survival and reproduction of the fittest members of the population, the maintenance of a population with diverse members, the inheritance of genetic information from parents, and the occasional mutation of genes.

These algorithms are best suited to solving combinatorial optimisation problems that cannot be solved using more conventional operational research methods. Thus, they can be applied to large, complex problems that are non-linear with multiple local optima. The first objective of this project is to develop the SewerNet application, which uses a GA to optimise the design and rehabilitation of sewer networks given the constraints placed by the UK regulators. SewerNet combines the object-orientated frameworks of: the OpenNet network model (Morley et al, 2000), the University of Exeter's Centre for Water Systems genetic algorithm library (Morley et al, 2000), and the hydraulic simulation module.

The Urban Pollution Management (UPM) procedure is well established in the United Kingdom as a way to evaluate the performance of the urban drainage system's effect on receiving waters' quality. However, although engineering solutions developed using the UPM procedure have been successful in meeting design criteria for water quality they have been less successful at delivering these benefits at least cost. The second objective of this project is to develop a novel approach to the design of cost effective solutions to urban water quality problems. The approach combines the concepts of UPM, simplified integrated urban catchment modelling and genetic algorithm optimisation within a software tool named Cougar. The use of Cougar to identify least cost engineering solutions to the pollution problems caused by combined sewer systems will be introduced through an illustrative example. The promising results achieved demonstrate the capability of the approach used to optimise designs in terms of cost and water quality performance.


  • Parker,M.A., D.A. Savic, G.A. Walters and Z. Kapelan (2000) SewerNet: A Genetic Algorithm Application for Optimising Urban Drainage Systems, presented at the International Conference on Urban Drainage via Internet,, May 18-25 (proceeding published on CD) p. 11.
  • Gill, E., M.A. Parker, D.A. Savic and G.A. Walters (2001), Cougar: A Genetic Algorithm and Rapid Integrated Catchment model-ling application for optimising capital investment in combined sewer systems, World Water & Environmental Resources Congress, May 20-24, Orlando, Florida, edited by Phelps, D. and G. Sehlke (proceeding published on CD), p. 10.

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