Optimal deployment of heterogeneous sensor networks for a hybrid point and barrier coverage application

To solve the defined problem, we first develop a multi-objective integer non-linear program (INLP) formulation. Since the INLP is non-convex it may not produce globally optimal solutions. For this purpose, using a special mapping technique, we reformulate the problem as a multi-objective integer linear program (ILP). Then, we employ a genetic algorithm (GA) metaheuristic to solve the problem. We then perform extensive simulation runs to measure and compare the performances of the proposed INLP, ILP and GA solution approaches. Our results indicate although the ILP is efficient for small size problems, it requires longer computing times to deliver globally optimal solutions. The INLP and GA, on the other hand, provide a balance between the solution quality and computation time for larger problem instances. The performance of the proposed hybrid modelling approach is demonstrated through sensitivity analysis runs.