An Adaptive Tabu Search Algorithm for the Multi-Objective Node Placement Problem In Heterogeneous Networks
Ons Abdelkhalek, Saoussen Krichen, Adel Guitouni · 2014
The Multi–objective Node Placement (MONP) problem focuses on extending an existing communication in- frastructure with new wireless heterogeneous network components while achieving cost effectiveness and ease of management. This extention aims to broaden the coverage and handle demand fluctuations. In this paper, the MONP problem is modelled as a multi–objective optimization problem with three objectives: maximiz- ing the communication coverage, minimizing active nodes and communication devices costs, and maximizing of the total capacity bandwidth in the network. As the MONP problem is N P–Hard, we present a meta– heuristic based on the Tabu Search approach specifically designed for multi–objective problems in wireless networks. We present an empirical validation of the model and the algorithm based on a selection of a real and large set of instances. We present also a performance comparison between the suggested algorithm and a multi–objective genetic algorithm (MOGA). All tests are performed on a real simulation environment for the maritime surveillance application.