I am looking for references to show that GA solutions do not necessarily converge to optimal solution to defend the use of an integer program, exact solution. I want to criticize heuristic and meta-heuristic algorithm, especially GA.
I think a book might be a good reference but not sure which one to use!
... and I bet you can quickly find articles that have implementations and cases of both, where they also compete on large-scale cases.
no free lunch theorem: https://en.wikipedia.org/wiki/No_free_lunch_in_search_and_optimization
Thanks .. I guess the NFL theorem is a good reference and argument
The NFL (not to confuse with the National Football League) is not a wild card to implement whatever stuff that comes to mind. Even in the case where an objective function isn't, say, differentiable, but at least Lipschitz continuous we do have an edge over methods that do not require anything - because they guarantee nothing either. I am referring to the flood of metaheuristics that have no natural stopping criteria beyond # iterations. In contrast Lipschitz continuity provides lower bounds that can be profitably utilized in decomposition methods, along the lines of Branch-and-Bound.
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