NDLI: A Hybrid Particle Swarm Optimization(PSO) Algorithm Schemes for Integrated Process Planning and Production Scheduling

Content Provider	IEEE Xplore Digital Library
Author	Fuqing Zhao Among Zhu Dongmei Yu Yahong Yang
Copyright Year	2006
Description	Author affiliation: Sch. of Comput. & Commun., Lanzhou Univ. of Technol. (Fuqing Zhao; Among Zhu; Dongmei Yu)
Abstract	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
Starting Page	6772
Ending Page	6776
File Size	110443
Page Count	5
File Format	PDF
ISBN	1424403324
DOI	10.1109/WCICA.2006.1714395
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-06-21
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Particle swarm optimization Scheduling algorithm Process planning Particle production Job shop scheduling Production systems Manufacturing systems Availability Demand forecasting Fuzzy systems fuzzy inference system particle swarm optimization(PSO) process planning production scheduling
Content Type	Text
Resource Type	Article

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