摘要
研究了以最小化最大完工时间为目标的有限缓冲区多产品厂间歇调度问题,提出了一种基于多种群粒子群优化(MPSO)的间歇调度算法。该算法采用多种群,增加了种群初始粒子的多样性,在每一代子种群并行进化的过程中引入移民粒子,使子种群之间相互影响和促进,避免算法过早地陷入局部最优,提高了算法的全局搜索能力;每代进化后选出子种群中的优秀粒子作为精华种群,并对其进行变邻域搜索(VNS),进一步提高了算法的收敛精度。通过对不同规模调度问题的仿真,以及与其它算法的对比,证明了该算法解决有限缓冲区多产品厂间歇调度问题的有效性和优越性。
For minimizing the total flow time of batch production,the bath scheduling problem with limited buffers was studied,and a batch scheduling algorithm based on the multi-swarm particle swarm optimization （MPSO） was proposed.The algorithm uses multiple swarms to increase the diversity of initial particles,and selects several good particles of each sub-swarm as the immigrant particles in the process of parallel evolution of sub-swarms to make the sub-swarms affect and promote each other,which prevents the result running into the local optimum prematurely and enhances the global research ability.It utilizes the variable neighborhood search （VNS） on the elite swarm consisting of each sub-swarm＇ s best particle to further improve its convergence accuracy.The effectiveness of this algorithm was verified by the simulation of different scales of scheduling and the comparison of its performance with other algorithms.The proposed algorithm can solve the batch scheduling problem with limited buffers.
出处
《高技术通讯》
CAS
CSCD
北大核心
2014年第8期866-873,共8页
Chinese High Technology Letters
基金
国家自然科学基金(61104178
61174040)资助项目
