I have been reading/studying on genetic algorithm/programming, and have implemented Traveling salesman problem.
TSP is basically a permutation/combination problem, and I can understand how GA helps to narrow down to the solution.
As far as I see GA is helpful in finding solution to
- similar permutation/combination problems and
- problems like pattern recognition.
Where/What are the other problem areas where GA could be applied and How(just provide a simple explanation) and What/Where GA can not be applied?
One case where I think GA can not applied are where there is no patterns, like Coin-Toss-Guess-Heads-Or-Tails Program, where outcome is purely luck.
Note: I am not looking for practical uses like printing circuit board or NLP. I am looking for what problems GA solves? or How to recognize that GA will help solve a certain problem instead of writing a complex algorithm.
Like TSP is a permutation/combination problem where possible solution could end up in 2.4 billion or more, and finding the right answer would be nearly impossible, Hence GA(or other optimization algorithm like simulated annealing) is useful in finding an optimal solution.