Three Local Search Meta-Heuristics for the Minimum Interference Frequency Assignment Problem (MI-FAP) in Cellular Networks

Abstract

The minimum interference frequency assignment problem (MI-FAP) plays an important role in cellular networks. MI-FAP is the problem of finding an assignment of a small number of frequencies to a large number of transceivers (TRXs) that minimizes the interferences level. The MI-FAP is known to be NP-Hard, thus it cannot be solved in polynomial time. To remedy this, researchers usually use meta-heuristic techniques to find an approximate solution in reasonable time. Here, the authors propose three meta-heuristics for the MI-FAP: a variable neighborhood search (VNS) and a stochastic local search (SLS) that are combined to obtain a third and a new one, which is called VNS-SLS. The SLS method is incorporated into the VNS process as a subroutine in order to enhance the solution quality. All three proposed methods are evaluated on some well-known datasets to measure their performance. The empirical experiments show that the proposed method VNS-SLS succeeds in finding good results compared to both VNS and SLS confirming a good balance between intensification and diversification.