@inbook {IOPORT.06065889,
    author       = {Sengupta, Soumyadip and Nasir, Md. and Mondal, Arnab Kumar and Das, Swagatam},
    title        = {An improved multi-objective algorithm based on decomposition with fuzzy dominance for deployment of wireless sensor networks.},
    year         = {2011},
    booktitle    = {Swarm, evolutionary, and memetic computing. Second international conference, SEMCCO 2011, Visakhapatnam, Andhra Pradesh, India, December 19--21, 2011. Proceedings, Part I},
    isbn         = {978-3-642-27171-7},
    pages        = {688-696},
    publisher    = {Berlin: Springer},
    doi          = {10.1007/978-3-642-27172-4_81},
    abstract     = {Summary: The aim of this paper is to find a deployed sensor node arrangement to maximize the area of coverage, minimize the net energy consumption, maximize the network lifetime, and minimize the number of deployed sensor nodes maintaining connectivity between each sensor node and the sink node for proper data transmission. We have also assumed tree structure of communication between the deployed nodes and the sink node for data transmission. We have modeled the sensor node deployment problem as a multi-objective constrained problem maintaining all the above requirements. We have proposed a new fuzzy dominance based decomposition technique called MOEA/DFD and have compared its performance on other contemporary state-of-arts in multi-objective optimization field like MOEA/D and NSGAII. The algorithm introduces a fuzzy Pareto dominance concept to compare two solutions and uses the scalar decomposition method only when one of the solutions fails to dominate the other in terms of a fuzzy dominance level. MOEA/DFD performs better than all other algorithms.},
    identifier   = {06065889},
}