TY - JFULL AU - Michiharu Maeda and Shinya Tsuda PY - 2011/12/ TI - Particle Swarm Optimization with Reduction for Global Optimization Problems T2 - International Journal of Mathematical and Computational Sciences SP - 1720 EP - 1725 VL - 5 SN - 1307-6892 UR - https://publications.waset.org/pdf/15383 PU - World Academy of Science, Engineering and Technology NX - Open Science Index 59, 2011 N2 - 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. ER -