Cloud Particles Evolution Algorithm

• Main Authors: Wei Li, Lei Wang, Qiaoyong Jiang, Xinhong Hei, Bin Wang
• Format: Article
• Language: English
• Published: Hindawi Limited 2015-01-01
• Series: Mathematical Problems in Engineering
• Online Access: http://dx.doi.org/10.1155/2015/434831

Many evolutionary algorithms have been paid attention to by the researchers and have been applied to solve optimization problems. This paper presents a new optimization method called cloud particles evolution algorithm (CPEA) to solve optimization problems based on cloud formation process and phase transformation of natural substance. The cloud is assumed to have three states in the proposed algorithm. Gaseous state represents the global exploration. Liquid state represents the intermediate process from the global exploration to the local exploitation. Solid state represents the local exploitation. The cloud is composed of descript and independent particles in this algorithm. The cloud particles use phase transformation of three states to realize the global exploration and the local exploitation in the optimization process. Moreover, the cloud particles not only realize the survival of the fittest through competition mechanism but also ensure the diversity of the cloud particles by reciprocity mechanism. The effectiveness of the algorithm is validated upon different benchmark problems. The proposed algorithm is compared with a number of other well-known optimization algorithms, and the experimental results show that cloud particles evolution algorithm has a higher efficiency than some other algorithms.