Sometimes we as engineers fall into the trap of searching for the one best solution to a problem. Algorithmically speaking I suspect this is probably NP-complete. This places it in the same category as the traveling salesman and knapsack problems in terms of complexity to solve.
For anyone who is familiar with these types of problems you should realize the futility of trying to find the best solution. Instead what we should be doing is attempting to come up with a measure that says that a solution is good enough.
Almost every problem has multiple qualitative variables such as ease of implementation, speed of execution, simplicity of maintenance, etc. And many problems have qualitative solutions, such as deciding whether one user interface design is better than another.
When you are working on a problem a good guideline to follow is to ask yourself whether the solution at the moment is good enough to satisfy minimum requirements in all areas. Then ask yourself if you can see an obvious modification that significantly improves one or more of these areas that doesn't significantly erode any other areas. If you are only seeing marginal gains in any area or the work to make it better is difficult, then you are probably done.
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