A novel multi-objective coverage optimization memetic algorithm for directional sensor networks

For the target problem of a directional wireless sensor network, the greedy algorithm can easily fall into the local optimal solution, whereas the genetic algorithm must forecast the lifetime of the upper bound of the network. We propose a novel multi-objective coverage optimization memetic algorithm that encodes the solutions as chromosomes and simulates the biological evolution process in search for a favourable solution to address the aforementioned problems. Experimental results show that the proposed algorithm can prolong the network lifetime more effectively than similar heuristic algorithms in other studies.