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2008 International Symposium on Computational Intelligence and Design
Workshop Material Handling System Lean Planning Based on Genetic Algorithm
October 17-October 18
ISBN: 978-0-7695-3311-7
| ASCII Text | x | ||
| Lu Xiaohong, Jia Zhenyuan, Wang Fuji, Liu Wei, "Workshop Material Handling System Lean Planning Based on Genetic Algorithm," Computational Intelligence and Design, International Symposium on, vol. 1, pp. 261-264, 2008 International Symposium on Computational Intelligence and Design, 2008. | |||
| BibTex | x | ||
| @article{ 10.1109/ISCID.2008.80, author = {Lu Xiaohong and Jia Zhenyuan and Wang Fuji and Liu Wei}, title = {Workshop Material Handling System Lean Planning Based on Genetic Algorithm}, journal ={Computational Intelligence and Design, International Symposium on}, volume = {1}, year = {2008}, isbn = {978-0-7695-3311-7}, pages = {261-264}, doi = {http://doi.ieeecomputersociety.org/10.1109/ISCID.2008.80}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, } | |||
| RefWorks Procite/RefMan/Endnote | x | ||
| TY - CONF JO - Computational Intelligence and Design, International Symposium on TI - Workshop Material Handling System Lean Planning Based on Genetic Algorithm SN - 978-0-7695-3311-7 SP261 EP264 A1 - Lu Xiaohong, A1 - Jia Zhenyuan, A1 - Wang Fuji, A1 - Liu Wei, PY - 2008 KW - heavy weight parts KW - lean production KW - material handling KW - genetic algoritm VL - 1 JA - Computational Intelligence and Design, International Symposium on ER - | |||
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ISCID.2008.80
There exists severe wastes in the material handling system of the heavy weight parts machining workshop, which mainly includes the waste of work areas' latency time and the waste of the material handling device's moving distance that caused by frequent circular and reverse routes. To eliminate the waste, a new heavy weight parts machining workshop material lean scheduling method is advanced. The initial universal response scheduling scheme of the heavy weight parts handling system based on genetic algorithm resolves the shortest response route problem when the material handling equipment responds to the requests from all the work areas at the beginning of a workday, which is being restricted to working procedures and the requests of as few as possible blank line. The simulation result shows that the designed new scheduling method is superior to the traditional ones evidently.
Index Terms:
heavy weight parts, lean production, material handling, genetic algoritm
Citation:
Lu Xiaohong, Jia Zhenyuan, Wang Fuji, Liu Wei, "Workshop Material Handling System Lean Planning Based on Genetic Algorithm," iscid, vol. 1, pp.261-264, 2008 International Symposium on Computational Intelligence and Design, 2008
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