Wireless LAN access point placement using a multi-objective genetic algorithm

This paper presents the use of a multiobjective genetic algorithm (MOGA) for solving an access point placement problem in a wireless LAN. The aim is to maximize signal coverage over the interested area. The problem has been formulated as a multiobjective optimization problem where the decision variables are derived from the locations of the access points in the target area. The objectives consist of the number of access points and the average SNR over the whole area. The major advantage of using MOGA is that multiple optimal placement configurations for different numbers of access points can be obtained from a single run. A set of solutions provides more alternatives to the network designer. The simulation results indicate that the MOGA is capable of generating a placement result which is superior to that produced using standard placement techniques. In addition, the result assessment has been confirmed using statistical and analyzed data profile.