A comparative study of Multiobjective Evolutionary Algorithms for Wireless Local Area Network design

Abstract

This manuscript presents a comparative study between three Multiobjective Evolutionary Algorithms (NSGA-II, GDE3, and MOEA/D-DE) on Wireless Local Area Networks design. The considered problem consists on defining the positions, quantity, channels, and load balance of access points to be installed. Problem features such as equipment limitations, traffic demand, and minimum coverage level required are modeled as constraints. The used algorithms were tested in two scenarios, considering different network profiles. The results show that the developed approach for WLAN planning can help a network designer to define good Wi-Fi projects, improving the signal level, network balance, and reducing interference.