DocumentCode
1775381
Title
Design of an evolutionary multi-objective optimization scheduling system for a screw manufacturer
Author
Tung-kuan Liu ; Yeh-Peng Chen ; Po-Han Lai ; Jyh-Hong Chou
Author_Institution
Inst. of Eng. Sci. & Technol., Nat. Kaohsiung First Univ. of Sci. & Technol., Kaohsiung, Taiwan
fYear
2014
fDate
18-20 June 2014
Firstpage
600
Lastpage
603
Abstract
The intelligent scheduling system has been proposed in this study and successfully applied to the scheduling of a screw manufacturer located at Taiwan, we aim added a concept of multi-objective optimization into practical scheduling system to promote the efficient of schedule and production. In order to meet user´s requirement, an improved genetic algorithm (GA) with a multi-objective design was adopted as a core technique of this intelligent system. It differs from traditional GA scheduling solution, our model capable of avoided incorrectly assigned a job to infeasible machine; thus, special designs in evolution process of GA are not required. A real case study was introduced in this paper, and the proposed model has been tested with 100 work orders, the empirical results were indicated that the proposed approach outperforms manual scheduling, regardless of the total orders completed time, machine retooling times, and the average load rate of machine.
Keywords
fasteners; genetic algorithms; scheduling; GA scheduling solution; average load rate; evolution process; evolutionary multiobjective optimization scheduling system; genetic algorithm; intelligent scheduling system; machine retooling times; multiobjective design; screw manufacturer; Biological cells; Fasteners; Genetic algorithms; Job shop scheduling; Manuals; Optimization; encode; evolutionary; flexible job scheduling; genetic algorithms; multi-objective optimization;
fLanguage
English
Publisher
ieee
Conference_Titel
Control & Automation (ICCA), 11th IEEE International Conference on
Conference_Location
Taichung
Type
conf
DOI
10.1109/ICCA.2014.6870987
Filename
6870987
Link To Document