A Multi-objective Rotation Optimization Based on GA for Heterogeneous Strong Barrier

Abstract

An important issue for directional sensor network monitoring and detection is how to repair gaps in strong barrier and improve the barrier coverage. To address this problem, we study the optimization problem of heterogeneous barrier coverage with different sensing radii, sensing angles and rotation directions. We propose a rotation optimization based on GA, including distributed gap judgment algorithm, interval intersection judgment, a new chromosome encoding representation, and combining crossover operators. Its principle is to mend the barrier gaps by rotating the heterogeneous sensors, to achieve the optimization objectives of maximum coverage rate, minimum gap rate. The simulation results demonstrate its effectiveness and superiority.