流程时间 meaning in Chinese
flow time
lead time
Examples
- To resolve resource scheduling problem efficiently in manufacturing grid , a multi - objective optimization mathematical model was put forward , which was based on task time , machining quality , cost and service quality
摘要为有效地解决制造网格中的资源调度问题，提出了以任务流程时间、加工质量、流程成本和服务质量为目标的多目标优化数学模型。 - At the same time , in order to maintain good fabrication quality , shorten the process time and meet the required due date , it is absolutely necessary to have good rework strategies for wafer rework so as to make up the wafer defects in the photolithography area
为了顾及生产中在制品水平量、产品生?流程时间、产品交期等目标，必须要有良好的再加工策略处理晶圆的再加工。 - A modified genetic algorithm ( mga ) framework was developed and applied to the flowshop sequencing problems with objective of minimizing mean total flowtime . to improve the general genetic algorithm routine , two operations were introduced into the framework . firstly , the worst points were filtered off in each generation and replaced with the best individuals found in previous generations ; secondly , the most promising individual was selectively cultivating if a certain number of recent generations have not been improved yet . under conditions of flowshop machine , the initial population generation and crossover function can also be improved when the mga framework is implemented . computational experiments with random samples show that the mga is superior to general genetic algorithm in performance and comparable to special - purpose heuristic algorithms . the mga framework can also be easily extended to other optimizations even though it will be implemented differently in detail
提出了一个改进遗传算法的结构，并且应用于带有目标是最小平均总流程时间的流水调度排序中.为了改进一般遗传算法的程序，两个新的操作被引进到这个操作中.这两个操作为： 1 )过滤操作：过滤掉在每一代中的最坏的个体，用前一代中的最好的个体替代它； 2 )培育操作：当在一定代数内算法不改进时，选择一个培育操作用于培育最有希望的个体.通过大量的随机产生的问题的例子的计算机实验显示出，提出的算法的性能明显好于一般遗传算法，并且和此问题的最好的专门意义的启发式算法相匹配.新的mga框架很容易扩展到其它最优化当中，只是实施的详细的步骤有所不同