I am working on a very large scale problem, I have an heuristic that gives a reasonably good solution in addition to the Genetic Algorithm heuristic which performs very well. I was wondering if there is any gain in pre-seeding the GA with the heuristics solution and if so how.
Thanks 2t
That very much depends on the heuristic, and your problem.
If you know this heuristic has a tendency of getting close to the global optimum, then it may be a good idea, as the GA may explore "around" this solution and find an optimal/closer to optimal solution.
The problem is, that when you pre-seed the GA with a good solution, it will have a huge advantage over other randomly generated solutions and will probably be selected many times to perform crossover, which means, if the heuristic gave you a local optimum, you might draw the GA towards that solution.
Another idea is to seed the GA in the middle of the process. let it run for half the generations and then inject it with the heuristic solution. then you have a smaller chance of dragging it to the heuristic solution if it was only a local optimum.
In general, since we're talking about heuristics and probabilistic models, it's better to benchmark all possibilities and see what works best for you, as these statements are usually problem-dependent.