Abstract
In this paper the Minimum Hitting Set (MHS) problem is considered. The problem is solved by a genetic algorithms (GA) that uses binary encoding and standard genetics operators adapted to the problem. In proposed implementation all individuals are feasibility by default, so search is directed into the promising regions. The overall performance of the GA implementation is improved by caching technique. Local search optimization is used to refine the solutions explored by GAs. The algorithm is tested on standard instances from the literature. The obtained results are also compared with the results of existing methods for solving MHS in order to assess their merits.
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