title: Multi-objective optimization method needed
body: <p><strong>EDIT: In lieu of other suggestions, I've decided to play around with the <a href="http://code.google.com/p/deap/" rel="nofollow noreferrer">Python DEAP framework</a> until I come up with something usable. Hopefully this helps people with a similar problem.</strong></p>
  
  <p>I am implementing a system in which we need to do multi-objective optimization for a client, as follows:</p>
  
  <p>A manufacturing system has to produce N parts (of the same kind) by welding. For this, a certain material can be chosen, a welding method, and the number of welding points to use for building each part. The image below shows the parameters of the problem and their interdependencies: </p>
  
  <p><img src="https://i.stack.imgur.com/eecu7.jpg" alt="enter image description here"></p>
  
  <p>I can play with values for</p>
  
  <pre><code>material
  welding method
  number of spot welding points
  </code></pre>
  
  <p>I need to find the combination of material, welding method and number of welding points/part that <em>minimizes</em> the cost and <em>maximizes</em> the stability.</p>
  
  <p>I was thinking of using an evolutionary algorithm approach. 
  However, my background is not in optimization, so, if someone could suggest a more specific algorithm that's suited for this problem, it would be really helpful.</p>