I'm trying to use GA solve the quadratic assignment problem (QAP). We're planning on using it to be able to provide good solutions when using branch and bound becomes impossible, and as a requirement, I have to make it work as if it "improved" an existing solution.
The problem is of course in generating the initial population. I want to ensure diversity as well as good fitness, but the starting individuals, somehow, have to come from a single input individual (it's going to be a good one, in terms of fitness).
How should I go about this? I've thought about creating an initial population consisting on half (or some proportion) of individuals similar to the initial one, and then adding the other half of new randomly (using some heuristic) generated individuals, to combine my solution with other parts of the solution space. Is this a good approach? If so, anny recommendations on the random heuristic to search for the new random individuals?