摘要
传统复杂工序流程整合算法中难以将复杂的工序流程转化成高效、新颖的且能适应各类操作者使用的简化流程。对此提出了一种基于多目标最优时效均衡的复杂工序流程整合算法。把工序整合中的工序动态选择的全局最优问题转换为一个不同目标的均衡,同时产生一组满足多目标均衡条件的工序流程集合,最终选择出最优工序流程。在选取最优工序的算法中加入基因遗传优化算法,使最终结果可以快速准确收敛,同时也提高了计算的精度。仿真实验中,对复杂工序流程的整合中,得到了时间与效率最优的整合方法。研究结果表明新算法在复杂工序流程整合领域具有较好的推广应用前景。
Integrating process in the process of dynamic selection global optimal equilibrium problem is converted to a dif-ferent goal, at the same time produce a set of satisfy the equilibrium conditions of the collection process flow, finally choose the optimal process flow. In selecting the optimal process of genetic optimization algorithm were added to the algorithm, which makes the final result is precise and fast convergence, but also improve the precision of calculation. Simulation exper-iments, the complex integration of process flow, obtained the optimal integration of time and efficiency. Research results show that the new algorithm in complex integration process flow field has a good application prospect.
出处
《科技通报》
北大核心
2014年第6期85-87,共3页
Bulletin of Science and Technology
关键词
整合算法
工序
全局最优
复杂工序流程
integrating algorithm
process
the global optimal
complex process flow
作者简介
李海蓉（1982-），女（汉族），四川广安人，博士研究生，研究方向：现代信息处理新技术。
