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===SWMM5-EA a tool for teaching evolutionary algorithms for water professionals===

==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 [[wikipedia:Confucius|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 [http://orange.biolab.si/ orange] to teach elementary datamining techniques and use [http://www.ra.cs.uni-tuebingen.de/software/JavaNNS/welcome_e.html JavaNNS) to teach [[wikipedia:Artificial Neural Networks|Artificial Neural Networks]]. But I could not find an acceptable tool to use in my teaching of GA. Once I wrote a [[wikipedia:console application|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 [[wikipedia:command prompt|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 [[wikipedia:SuDS|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. 


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