DocumentCode
482161
Title
A Genetic Algorithm Approach for Optimum Operator Assignment in CMS
Author
Azadeh, Ali ; Kor, Hamrah ; Hatefi, Seyed-Morteza
Author_Institution
Dept. of Ind. Eng., Univ. of Tehran, Tehran
Volume
1
fYear
2009
fDate
22-24 Jan. 2009
Firstpage
42
Lastpage
46
Abstract
This paper presents a decision making approach based on a hybrid GA for determining the most efficient number of operators and the efficient measurement of operator assignment in cellular manufacturing system (CMS).The objective is to determine the labor assignment in CMS environment with the optimum performance. We use The GA for getting near optimum ranking of the alternative with accordance to fitness function. Also, the GA approach is performed by employing the number of operator, average lead time of demand, average waiting time of demand, number of completed parts, operator utilization and average machine utilization as attributes, and Entropy method for determining the weight of attributes. Furthermore, values of the attributes procured by means of simulation.
Keywords
cellular manufacturing; decision making; genetic algorithms; average machine utilization; cellular manufacturing system; decision making; entropy method; hybrid genetic algorithm; labor assignment; near optimum ranking; optimum operator assignment; Cellular manufacturing; Collision mitigation; Computer aided manufacturing; Decision making; Entropy; Genetic algorithms; Genetic engineering; Paper technology; Simultaneous localization and mapping; Uncertainty; CMS; Entropy method; Genetic Algorithm; Visual SLAM; decision making; simulation;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Engineering and Technology, 2009. ICCET '09. International Conference on
Conference_Location
Singapore
Print_ISBN
978-1-4244-3334-6
Type
conf
DOI
10.1109/ICCET.2009.211
Filename
4769423
Link To Document