@article{(Open Science Index):https://publications.waset.org/pdf/15383,
	  title     = {Particle Swarm Optimization with Reduction for Global Optimization Problems},
	  author    = {Michiharu Maeda and  Shinya Tsuda},
	  country	= {},
	  institution	= {},
	  abstract     = {This paper presents an algorithm of particle swarm
optimization with reduction for global optimization problems. Particle
swarm optimization is an algorithm which refers to the collective
motion such as birds or fishes, and a multi-point search algorithm
which finds a best solution using multiple particles. Particle
swarm optimization is so flexible that it can adapt to a number
of optimization problems. When an objective function has a lot of
local minimums complicatedly, the particle may fall into a local
minimum. For avoiding the local minimum, a number of particles are
initially prepared and their positions are updated by particle swarm
optimization. Particles sequentially reduce to reach a predetermined
number of them grounded in evaluation value and particle swarm
optimization continues until the termination condition is met. In order
to show the effectiveness of the proposed algorithm, we examine the
minimum by using test functions compared to existing algorithms.
Furthermore the influence of best value on the initial number of
particles for our algorithm is discussed.},
	    journal   = {International Journal of Mathematical and Computational Sciences},
	  volume    = {5},
	  number    = {11},
	  year      = {2011},
	  pages     = {1721 - 1725},
	  ee        = {https://publications.waset.org/pdf/15383},
	  url   	= {https://publications.waset.org/vol/59},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 59, 2011},