总流程 meaning in English
main-process stream
Examples
- ( 2 ) on the basis of detailed analysis of the characteristics , structure model , basic theory and technology of scm , the theoretic model and implementing method based on integrated scm are proposed to meet the needs of new ave - oriented erp system . in addition , the improved process of production plan , the new strategy of alliance inventory based on coordination center , the new purchase business principle driven by order and the total program of enterprise business activities based on internet in scm are also presented in order to solve key problems from the integration inside an enterprise to the integration among enterprises , which are how to use mrpii system to realize scm among enterprises
( 2 )在详细剖析供应链及其管理的特点、结构模型和基本理论及其技术的基础上，提出了集成化供应链管理的理论模型和实施方法，较好地满足了面向动态联盟企业的新一代erp系统的要求，同时还提出了供应链管理scm环摘要境下的生产计划与控制的改进流程、基于协调中心的联合库存控制新策略、订单驱动的采购业务原理和基于internet的企业业务总流程，以便解决企业内集成向企业问集成发展过程中的核心问题? ?如何通过应用mrpll系统来实现企业问的供应链管理。 - 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