Journal of Engineering and Applied Sciences
ISSN: Online 1818-7803ISSN: Print 1816-949x
Abstract
Wireless Sensor Network Deployment or (WSND) is considered as an active research subject. Its goal is to plan the sensor network’s configurations to achieve maximum coverage and lifetime while incurring minimum cost. Meta-heuristic searching optimisation was utilised to solve this problem. However, the complex optimisation surface and the multi-objective characteristic of this problem necessitate the development of customisable multi-objective meta-heuristic searching optimisation. For this study, Lagged Multi-Objective Jumping Particle Swarm Optimisation (LMOJPSO) was formulated to solve WSND. LMOJPSO is considered as a new multi-objective optimisation for WSND. Conduct of the optimisation search took place by utilising three kinds of Pareto front: iteration, global and local. Furthermore, the lag is incorporated in the algorithm for iteration of the Pareto front. From the MOO perspective this offers better Pareto solutions. Results of its comparison with state-of-the-art approach NSGA-II reveals that LMOJPSO is better compared to it.
How to cite this article:
Ali Noori Kareem, Ong Bi Lynn and Hasna Ahmad. Mathematical Function and Algorithms Optimisation for Wireless Sensor Networks.
DOI: https://doi.org/10.36478/jeasci.2019.6668.6674
URL: https://www.makhillpublications.co/view-article/1816-949x/jeasci.2019.6668.6674