A Mized Ant Colony Algorithm for Function Optimization

摘要：

Ant colony algorithm(ACA) is a novel simulated evolutionary algorithm, which is based on the process of ants in the nature searching for food. ACA has many good features in optimization, but it has the limitations of stagnation and poor convergence, and is easy to fall in local optimization. Pointing at these disadvantages, Artificial fish-swarm algorithm(AFSA) is presented to conquer the disadvantages. The algorithm of rapid search capability of AFSA and the good search characteristics of ACO, and the convergent speed of the presented algorithm avoiding being trapped in local optimum is improved.

关键词： ant colony algorithm artificial fish-swarm algorithm function optimization

作者: SHI Hong-yan BEI Zhao-yu

作者单位: School of Information Science & EngineeringShenyang University of Technology 110178China

会议类型: 国际会议

会议名称: 2009年中国控制与决策会议(2009 Chinese Control and Decision Conference)

会议地点: 广西桂林

会议语种:英文

页码: 3883-3887

在线出版日期: 2009-06-17（万方平台首次上网日期，不代表论文的发表时间）