Boosting an evolution strategy with a preprocessing step: application to group scheduling problem in directional sensor networks

This paper presents a two-membered evolution strategy based approach to address the total rotation minimization problem (TRMP) pertaining to directional sensor networks. TRMP is an NP$\mathcal {N}\mathcal {P}$-hard problem. Performance of the proposed approach is enhanced by employing a pre-processing step that utilizes a constructive heuristic and the concept of opposite solutions. We have compared our approach with the best approach available in the literature. The experimental results demonstrate our approach to be highly effective with substantial gain in terms of solution quality, in comparison to the best approach available in the literature. However, our approach requires more time in comparison to this approach.