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New Data from C.W. Chou et al Illuminate Findings in Algorithms (A Multiobjective Hybrid Genetic Algorithm for TFT-LCD Module Assembly Scheduling)

September 9, 2014



By a News Reporter-Staff News Editor at Journal of Mathematics -- Investigators publish new report on Algorithms. According to news originating from Fukuoka, Japan, by VerticalNews correspondents, research stated, "The thin-film transistor-liquid crystal display (TFT-LCD) module assembly production is a flexible job-shop scheduling problem that is critical to satisfy the customer demands on time. On the module assembly shop floor, each workstation has identical and non-identical parallel machines that access the jobs at various processing velocities depending on the product families."

Our news journalists obtained a quote from the research, "To satisfy the various jobs, the machines need to be set up as the numerous tools to conduct consecutive products. This study aims to propose a novel approach to address the TFT-LCD module assembly scheduling problem by simultaneously considering the following multiple and often conflicting objectives such as the makespan, the weighted number of tardy jobs, and the total machine setup time, subject to the constraints of product families, non-identical parallel machines, and sequence-dependent setup times. In particular, we developed a multiobjective hybrid genetic algorithm (MO-HGA) that hybridizes with the variable neighborhood descent (VND) algorithm as a local search and TOPSIS evaluation technique to derive the best compromised solution. To estimate the validity of the proposed MO-HGA, experiments based on empirical data were conducted to compare the results with conventional approaches. The results have shown the validity of this approach. This study concludes with a discussion of future research directions. Note to Practitioners-Because of short product lifecycles, cycle time reduction and on-time delivery are crucial in high-tech industries such as the TFT-LCD and semiconductor manufacturing. To address these needs in real settings, a novel multiobjective hybrid genetic algorithm (MO-HGA) was developed, hybridizing with a variable neighborhood descent (VND) algorithm as a local search and TOPSIS technique to select the best compromised solution for the TFT-LCD module assembly scheduling problem. Experiments have shown practical viability of this approach."

According to the news editors, the research concluded: "Future studies can be done to extend the developed solution to other high-tech manufacturing industries."

For more information on this research see: A Multiobjective Hybrid Genetic Algorithm for TFT-LCD Module Assembly Scheduling. IEEE Transactions on Automation Science and Engineering, 2014;11(3):692-705. IEEE Transactions on Automation Science and Engineering can be contacted at: Ieee-Inst Electrical Electronics Engineers Inc, 445 Hoes Lane, Piscataway, NJ 08855-4141, USA. (Institute of Electrical and Electronics Engineers - www.ieee.org/; IEEE Transactions on Automation Science and Engineering - ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=8856)

The news correspondents report that additional information may be obtained from C.W. Chou, Fuzzy Log Syst Inst, Fukuoka 8200067, Japan. Additional authors for this research include C.F. Chien and M. Gen.

Keywords for this news article include: Fukuoka, Japan, Asia, Algorithms, Genetics

Our reports deliver fact-based news of research and discoveries from around the world. Copyright 2014, NewsRx LLC


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Source: Journal of Mathematics


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