Multiobjective frequency assignment problem using the MO-VNS and MO-SVNS algorithms

Abstract

In GSM networks, the Frequency Assignment is a critical task for the mobile operators. In this paper we study different multiobjective metaheuristics to address the Frequency Assignment problem (FAP). In fact, solving optimization problems with multiple (often conflicting) objectives is, generally, a very difficult goal. This is the scenario in the FAP, where it is sought an assignment of frequencies to a number of transmitters in as efficient way as possible. The multiobjective FAP tries to minimize the number of interferences caused when a limited number of frequencies needs to be assigned to a high number of transceivers. Besides these interferences costs, the separation costs are also considered. Our approach uses a Multiobjective Variable Neighborhood Search (MOVNS) algorithm and also its variant Multiobjective Skewed Variable Neighborhood Search (MO-SVNS). Two real-world GSM networks were used, currently being in operation, to test the presented metaheuristics.