SWMM5 EA

Background

I have been teaching the application of Evolutionary Algorithms (EA) like Genetic Algorithms (GA) since 2006 in two of my courses at UNESCO-IHE (Urban Drainage and Water Asset Management). I think there is a lot of truth in the quotation commonly attributed to Confucius (551–479 BCE): "What I hear I forget, what I see I remember, what I do I understand.". I try to apply this in teaching as much as possible -- let the learners do something and learn.

For many of my needs I found excellent tools on the net: For example, I use orange to teach elementary datamining techniques and use [http://www.ra.cs.uni-tuebingen.de/software/JavaNNS/welcome_e.html JavaNNS) to teach Artificial Neural Networks. But I could not find an acceptable tool to use in my teaching of GA. Once I wrote a console application using C langauge to try to do this. But, modern day students are not often comfortable with working with an application that needs opening a command prompt to use.

Finally I thought of biting the bullet and write one myself. That is SWMM5-EA.

What it does

SWMM5 EA is a simple application to demonstrate how genetic algorithms can be used to solve optimization problems in the field of urban drainage. Typical problems it can solve include:

• Find the optimal pipe/channel sizes for a drainage network to handle a flow of a given magnitude.
• Sizing of SuDS systems for the same purpose.
• Cost-benefit optimization of interventions.

Limitations

SWMM5 EA is a teaching tool. It has several limitations, by design.

• The drainage model is only 1-D, there's no inundation (2-D) model. (Things need to be kept simple)
• At the moment it is not designed to do whole-life cost optimization.
• At the moment no multi-objective optimization stuff.