摘要
为解决家纺企业的生产调度问题,设计了一种新颖的遗传算法.算法采用自然的编码方式,能有效地反映实际调度方案,即清楚反映出每日每机器加工产品的顺序和数量,通过提出一种新的基于浓度的种群多样性更新选择方法,提高了种群多样性,且利用局部搜索算法对每子代得到的调度方案进行了局部调整,改善了种群质量,加快了收敛速度.仿真结果表明,此算法是有效的,适用于解家纺企业实际生产调度问题.
In order to solve production scheduling problems in textile manufacturing industry, a novel genetic algorithm based on the natural encoding method is presented. For the proposed algorithm, the natural encoding method can effectively reflect the scheduling scheme, i.e. sequences and quantities of these processed products from each machine every day. And a local search algorithm is utilized to facilitate the exploitation of search space. Especially, a new diversity selection scheme based on concentration is suggested to maintain the diversity of the population and improve its convergence. Simulation results show that the proposed algorithm is effective, and can be applied to solve practical production scheduling problems of textile manufacturing industry.
出处
《哈尔滨工业大学学报》
EI
CAS
CSCD
北大核心
2009年第6期229-231,共3页
Journal of Harbin Institute of Technology
基金
国家自然科学基金资助项目(40405019)
浙江省教育厅基金资助项目(20051436)
关键词
生产调度
遗传算法
家纺企业
production scheduling
genetic algorithm
textile manufacturing industry
