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@article{143935,
        author = {V. Suganthi and R.Pandiammal and Shinoj CM},
        title = {Modified Patricle Swarm Optimization},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {3},
        number = {4},
        pages = {238-241},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=143935},
        abstract = {This paper present the Modified approaches of Particle Swarm Optimization (PSO) with Genetic Algorithm (GA). PSO and GA are Population   based heuristic search technique which can be used tosolve   the optimization problems modeled on the concept of Evolutionary Approach. In standard PSO, the non-oscillatory route can   quickly cause a particle to stagnate and also it may prematurely converge on suboptimal solutions that are not even guaranteed to be local optimum. In this paper the modification strategies are proposed in PSO using GA. Experiment results are examined with benchmark functions and results show that the proposed modified PSO models outperform the standard PSO.},
        keywords = { Particle Swarm Optimization (PSO), Genetic Algorithm (GA)},
        month = {},
        }