title: 2D shape optimization through genetic algorithms
body: <p>I just recently started learning about genetic algorithms and am now trying to implement them in 2D shape optimization in physics simulaiton. The simulation produces a single scalar for each shape. (I guess this is kind of similar to boxcar2d <a href="http://boxcar2d.com/" rel="nofollow">http://boxcar2d.com/</a>)</p>
  
  <p>The 2D shapes are actually the union of several 2D "sub shapes." Each subshape is stored as an list of angles/radii. The 2D shape is then stored as a list of subshape lists. This serves as my chromosone right now.</p>
  
  <p>Right now for fitness, I will probably use the scalar the simulation produced. My question is, how should I go about the selection and reproduction process? Would tournament be more appropriate, or would I want to use truncation in combination with the proportional selection? Also, how do you find a good mutation rate/population size, etc</p>
  
  <p>sorry for so many questions but thanks in advance. I just don't really know where to start.</p>