随机装卸工问题的新型混合粒子群算法  

New hybrid particle swarm optimization algorithm for stochastic loader problem

作　　者：王红[1] 赵培怡 

机构地区：[1]山东轻工业学院财政与金融学院,济南250100 [2]山东省教育招生考试院,济南250011

出　　处：《计算机工程与应用》2012年第24期192-196,共5页Computer Engineering and Applications

基　　金：教育部人文社科基金项目(No.12YJCZH303);中国博士后科学基金项目(No.2011M501149)

摘　　要：提出随机装卸工问题并将其转化为确定性问题,给出了其求解策略。针对粒子群算法简便实用但易过早收敛的问题,提出了一种结合人工免疫算法的新型混合粒子群算法,将该算法运用于求解随机装卸工问题。数值算例的计算结果表明:与基本粒子群算法相比,改进的粒子群算法在求解随机装卸工问题上表现出的求解精度和速度都十分理想。The stochastic loader problem is proposed and converted to a deterministic program.As a new computational method for the combinatorial optimization problem,the Particle Swarm Optimization algorithm is simple and effective,but it does suffer from the premature convergence.In order to overcome this problem,a new hybrid Particle Swarm Optimization algorithm combined with Artificial Immune Algorithm is proposed and used to solve the stochastic loader problem.Numerical examples show that compared with the basic Particle Swarm Optimization algorithm,the new hybrid particle swarm optimization algorithm has higher efficiency and reliability.

关 键 词：随机装卸工问题 粒子群算法 人工免疫 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]