Solving Maximal Covering Problem using Partitioned Intelligent Fish Algorithm

NP-Complete optimization problems are a well-known and widely used set of problems which surveyed and researched in the field of soft computing. Nowa days, because of the acceptable rate of achieving optimal or near-optimal solutions of the mentioned issues, using of nature-inspired algorithms are increasingly considered. One of the familiar proble ms in the field of NP problems is Maximal Covering Problem which has various applications of pure math ematics to determine the location of mobile network antennas or police stations. In this paper, we intr oduced a heuristic algorithm called Partitioned Art ificial Intelligent Fish Algorithm which using artificial f ish-search algorithm, logical partitioning of the s arch space of this algorithm to several sub-space and ch ange in motor functions in fishes, deals with the s uitable, innovative and fast solution of maximal covering pr oblem. The results of implementing this algorithm a nd comparing it with the performance of some the best known algorithms for solving NP problems will be represented by a very good performance of the propo sed algorithm.

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