A hybrid Particle Swarm Optimization(PSO) algorithm schemes for integrated process planning and production scheduling

被引：0
|
作者：
Zhao, Fuqing [1 ]
Zhu, Aihong [1 ]
Yu, Dongmei [1 ]
Yang, Yahong [2 ]
机构：
[1] Lanzhou Univ Technol, Sch Comp & Commun, Lanzhou 730050, Gansu, Peoples R China
[2] Lanzhou Univ Technol, Sch Civil Engn, Lanzhou 730050, Gansu, Peoples R China
来源：
WCICA 2006: SIXTH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION, VOLS 1-12, CONFERENCE PROCEEDINGS | 2006年
关键词：
particle swarm optimization(PSO); process planning; production scheduling; fuzzy inference system;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Process planning and production scheduling play important roles in manufacturing systems. Their roles are to ensure the availability of manufacturing resources needed to accomplish production tasks result from a demand forecast. In this paper, instead of choosing alternative machines randomly, the fuzzy inference system is being introduced for the purposes of choosing appropriate machines. Machines will be chosen based on the machine's reliability characteristics. This will ensure the capability of the machine in fulfilling the production demand. In addition, based on the capability information, the load for each machine is balanced by using the Particle Swarm Optimization (PSO). Simulation study shows that the system can be used as an alternative way of choosing machines in integrated process planning and scheduling.
引用
收藏
页码：6772 / +
页数：2
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