Iterated Local Search
Iterated local search techniques attempt to overcome the problem of local maxima by running the optimization procedure repeatedly, from different initial states.
If used with sufficient iterations, this kind of method will almost always find a global maximum.
The aim, of course, in running methods like this is to provide a very good solution without needing to exhaustively search the entire problem space.
In problems such as the traveling salesman problem, where the search space grows extremely quickly as the number of cities increases, results can be generated that are good enough (i.e., a local maximum) without using many iterations, where a perfect solution would be impossible to find (or at least it would be impossible to guarantee a perfect solution even one iteration of local search may happen upon the global maximum).
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Iterated Local Search
Iterated local search techniques attempt to overcome the problem of local maxima by running the optimization procedure repeatedly, from different initial states.
If used with sufficient iterations, this kind of method will almost always find a global maximum.
The aim, of course, in running methods like this is to provide a very good solution without needing to exhaustively search the entire problem space.
In problems such as the traveling salesman problem, where the search space grows extremely quickly as the number of cities increases, results can be generated that are good enough (i.e., a local maximum) without using many iterations, where a perfect solution would be impossible to find (or at least it would be impossible to guarantee a perfect solution even one iteration of local search may happen upon the global maximum).