Evolutionary cell planner

Much work has been done on the use of heuristic techniques for the optimization and planning of mobile networks [Xuemin Huang et al., 2000]-[Xuemin Huang, 2001]. Monte Carlo, genetic algorithm (GA) [D.E. Goldberg, 1989] and simulated annealing (SA) have been used for the purpose of cell planning with moderate success. In this paper, a proposed evolutionary learning technique [Y.H. Lee et al., 2004] is used for the optimization and cell planning. This technique is able to perform a heuristic search with intelligence; knowledge gained from information gathered from previously searched problem space. The success of this technique is attributed to its ability to evolve the cell planning design in an intelligent way with knowledge of the previously searched cell plans. In this paper, a simple example, with Singapore as the model, is used to illustrate the capability of the evolutionary cell planner.