@article{MAKHILLIJSSCEA201811128765,
    title = {Multi-Objective Modified Flower Pollination Algorithm for Maximizing
Lifetime in Wireless Sensor Networks},
    journal = {International Journal of System Signal Control and Engineering Application},
    volume = {11},
    number = {1},
    pages = {20-29},
    year = {2018},
    issn = {1997-5422},
    doi = {ijssceapp.2018.20.29},
    url = {https://makhillpublications.co/view-article.php?issn=1997-5422&doi=ijssceapp.2018.20.29},
    author = {Essam H. and},
    keywords = {Wireless Sensor Networks,sink node,modified flower pollination algorithm,multi-objective optimization,swarm intelligence,energy consumption,Pareto front},
    abstract = {All data collected by the sensor nodes is sent to sink nodes in the Wireless Sensors Networks
(WSNs). Therefore, location and the optimal number of the sink nodes has a significant impact according to
the various complexity factors, it can be addressed with optimization algorithms as an optimization problem. In
this study, a Multi-Objective Modified Flower Algorithm (MOMFPA) pollination has proposed to deal with the
problem of multiple sink nodes in WSN in order to attain the minimum number of multiple sink nodes with
reduced energy consumption to extend the lifetime of the WSN. To realize this, a fitness function has been
formulated to guarantee the balance between the sink nodes and energy consumption. Moreover, to assess
the performance of the proposed algorithm introduced here, it is simulated in different network sizes ranging
from 100-5000 nodes and the results proved that the proposed algorithm overcomes the two well-known
algorithms famous in the optimization domain such as Multi-Objective Differential Evolution (MODE) and
Multi-Objective Particle Swarm Optimization (MOPSO) in terms of the number of multiple sink nodes as well as
the low energy consumption. Eventually, the quantitative and qualitative results revealed that the proposed
MOMFPA significantly was able to find the optimal Pareto Front (PF) and provide a superior quality of
solutions.}
    }