In this paper, we propose a new cooperative algorithm based on tabu search (TS) and genetic algorithm (GA) in order to solve the global planning problem of Universal Mobile Telecommunications System (UMTS) networks. This problem has been shown to be NP-hard as it is composed of three different subproblems (each one being NP-hard): the cell planning problem, the access network planning problem and the core network planning problem. As a result, approximate algorithms are necessary in order to solve larger instances of the problem. Numerical results show that the cooperative algorithm can find solutions with an average gap of 0.24% with respect to the optimal solution in a reasonable amount of computation time. By combining TS and GA, we show that better results can be obtained than using each algorithm separately.
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