Author(s): Ashvini Kulkarni, Dr. Datta Parle
Published in: International Journal of Engineering Research & Technology
License: This work is licensed under a Creative Commons Attribution 4.0 International License.
Volume/Issue: Volume. 6 - Issue. 03 , March - 2017
Several optimization techniques are proposed in artificial intelligence. This paper we contrast performance of Swarm Intelligence based PSO search strategy to optimize the multiple objective functions. Experimental analysis also demonstrated the effect of the inertia weight for multiple objective functions in the algorithm. And optimize time for all particles are detected and calculated by Particle Swarm Optimization.
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