Apical-dominant particle swarm optim

Apical-dominant particle swarm optimization

Particle swarm optimization (PSO) is a new stochastic population-based search methodology by simulating the animal social behaviors such as birds flocking and fish schooling.Many improvements have been proposed within the framework of this biological assumption.However,in this paper,the search pattern of PSO is used to model the branch growth process of natural plants.It provides a different poten-tial manner from artificial plant.To illustrate the effectiveness of this new model,apical dominance phenomenon is introduced to construct a novel variant by emphasizing the influence of the phototaxis.In this improvement,the population is divided into three different kinds of buds associated with their performances.Furthermore,a mutation strategy is applied to enhance the ability escaping from a local optimum.Sim-ulation results demonstrate good performance of the new method when solving high-dimensional multi-modal problems.

作 者： Zhihua Cui Xingjuan Cai Jianchao Zeng Guoji Sun   作者單位： Zhihua Cui(State Key Laboratory for Manufacturing Systems Engineering, Xi'an Jiaotong University, Xi'an 710049, China;Division of System Simulation and Computer Application, Taiyuan University of Science and Technology, Taiyuan 030024, China)

Xingjuan Cai,Jianchao Zeng(Division of System Simulation and Computer Application, Taiyuan University of Science and Technology, Taiyuan 030024, China)

Guoji Sun(State Key Laboratory for Manufacturing Systems Engineering, Xi'an Jiaotong University, Xi'an 710049, China) 

刊 名： 自然科學(xué)進(jìn)展（英文版）  SCI 英文刊名： PROGRESS IN NATURAL SCIENCE  年，卷(期)： 2008 18(12)  分類號(hào)： N1  關(guān)鍵詞： Apical-dominance phenomenon   Particle swarm optimization   Branch growth model   High-dimensional multi-modal benchmarks