摘要
在求解一类带时间窗口的自动化生产单元调度问题时,基本粒子群算法易陷入局部极值点且收敛缓慢。针对这一问题,将混沌搜索技术引入至基本粒子群算法中,利用混沌运动搜索精度高、遍历性好的特点来改善基本粒子群算法易陷入局部极值点和收敛缓慢的缺点,从而提高粒子群算法的收敛速度和优化质量。首先给出了带时间窗口的自动化生产单元调度问题的混合整数规划模型,着重讨论了混沌粒子群调度算法的设计,包括编码方式、混沌初始化、混沌扰动和适应度函数计算等。对提出的算法进行了仿真验证,仿真结果表明在求解此类调度问题上,混沌粒子群算法比基本粒子群算法具有明显的优势。
When particle swarm optimization time window constraints, it often converges to （pso） a local is used to solve robotic cell scheduling problem with minimum and takes a long time. To overcome these problems, chaos search technique is introduced into PSO, because of its high precision and good ergodicity. With a mixed integer programming model presented for the problem, algorithm design is discussed, including encoding, chaos initialization, chaos perturbation, and fitness function calculation. instances are used to verify the proposed algorithm. It is shown that the chaos PSO is the basic PSO.
出处
《工业工程》
北大核心
2009年第6期90-95,共6页
Industrial Engineering Journal
基金
国家自然科学基金资助项目(50605052)
教育部"新世纪优秀人才支持计划"资助项目(NCET-06-0875)
关键词
自动化生产单元
调度
混沌
粒子群算法
robotic cells
scheduling
chaos
particle swarm optimization Randomly generated obviously superior to
