摘要
本文介绍一种适合任何规模的成组生产计划算法（KML）,其依据是关键机床负荷概念和改进的无回朔边界——分歧方法（IBBW）,理论分析和试算结果表明IBBW能够提供的结果比普通的探索法和无回朔边界——分歧法更接近优化,而且所需计算时间也不随工件数增加而迅速增加。在一个预定的生产周期中,KML算法在保证工件能够按期完成和关键机床全负荷的前提下,为一批零件生产提供最短提前时间。
An algorithm for large scale group scheduling problems has been developed using the concept of Key Machine Loading (KML) and an Improved Branch-and-Bound Without backtracking ( IBBW ) method. Analysis and experimental results indicate that IBBW can give solutions being closer to the optimum than those provided by heuristic and branch-and-bound without backtracking methods, and the computation time is not significantly increased with the job size. For a scheduling time period, the KML algorithm calculates a minimum lead time for a batch of jobs to guarantee that jobs can be completed on due-date and that the key machine tool has no idle time. An example of application of the KML algorithm is presented.
关键词
成组工艺
生产计划
最佳化
group technology, production planning, optimization.
