A Multiobjective Hybrid Genetic Algorithm for TFT-LCD Module Assembly Scheduling

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 t...

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Vydáno v:	IEEE transactions on automation science and engineering Ročník 11; číslo 3; s. 692 - 705
Hlavní autoři:	Che-Wei Chou, Chen-Fu Chien, Gen, Mitsuo
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York IEEE 01.07.2014 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	Assembly Assembly lines Crystals Genetic algorithms Job shop scheduling Job shops LCDs Liquid crystal displays Machine shops Modules Molybdenum Multiobjective genetic algorithm Parallel machines Scheduling Setup times Thin film transistors Thin films thin-film transistor-liquid crystal display (TFT-LCD) TOPSIS variable neighborhood descent Work stations Workstations
ISSN:	1545-5955, 1558-3783
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Abstract	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. 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.
AbstractList	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. 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.
Author	Gen, Mitsuo Chen-Fu Chien Che-Wei Chou
Author_xml	– sequence: 1 surname: Che-Wei Chou fullname: Che-Wei Chou email: cfchien@mx.nthu.edu.tw organization: Dept. of Ind. Eng. & Eng. Manage., Nat. Tsing Hua Univ., Hsinchu, Taiwan – sequence: 2 surname: Chen-Fu Chien fullname: Chen-Fu Chien organization: Dept. of Ind. Eng. & Eng. Manage., Nat. Tsing Hua Univ., Hsinchu, Taiwan – sequence: 3 givenname: Mitsuo surname: Gen fullname: Gen, Mitsuo organization: Dept. of Ind. Eng. & Eng. Manage., Nat. Tsing Hua Univ., Hsinchu, Taiwan
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Snippet	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...
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SubjectTerms	Assembly Assembly lines Crystals Genetic algorithms Job shop scheduling Job shops LCDs Liquid crystal displays Machine shops Modules Molybdenum Multiobjective genetic algorithm Parallel machines Scheduling Setup times Thin film transistors Thin films thin-film transistor-liquid crystal display (TFT-LCD) TOPSIS variable neighborhood descent Work stations Workstations
Title	A Multiobjective Hybrid Genetic Algorithm for TFT-LCD Module Assembly Scheduling
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