A Novel Two-level Genetic Algorithm for Integrated Process Planning and Scheduling

被引：0
|
作者：
Wan, Liang [1 ]
Li, Xinyu [1 ]
Gao, Liang [1 ]
Wen, Xiaoyu [1 ]
Wang, Wenwen [1 ]
机构：
[1] Huazhong Univ Sci & Technol, State Key Lab Digital Mfg Equipment & Technol, Wuhan 430074, Peoples R China
来源：
2013 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC 2013) | 2013年
关键词：
Process planning; scheduling; integrated process planning and scheduling; improved genetic algorithm;
D O I：
10.1109/SMC.2013.476
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
Process planning and scheduling are two important sub-systems in modern manufacturing system. In manufacturing system, the two sub-systems of process planning and scheduling have been treated sequentially or separately in traditional methods. To increase the effectiveness of system performance, there is an increasing need for deep research and application of integrated process planning and scheduling (IPPS) system. In this paper, a novel two-level genetic algorithm (TGA) is proposed to optimize the IPPS problem. Based on the previous work, deep research should be made on the IPPS problem. In this study, the flow chart of TGA based on the previous integrated optimization strategy has been proposed. Experiment studies have been conducted to verify the performance of the proposed algorithm. The experimental results show that the proposed algorithm for the IPPS is a promising and very effective method.
引用
收藏
页码：2789 / 2794
页数：6
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