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dc.contributor.author林慈盈en_US
dc.contributor.authorLin, Cih-Yingen_US
dc.contributor.author巫木誠en_US
dc.contributor.authorWu, Muh-Cherngen_US
dc.date.accessioned2014-12-12T01:31:47Z-
dc.date.available2014-12-12T01:31:47Z-
dc.date.issued2008en_US
dc.identifier.urihttp://140.113.39.130/cdrfb3/record/nctu/#GT079633533en_US
dc.identifier.urihttp://hdl.handle.net/11536/42888-
dc.description.abstract本研究探討考慮跨廠與整備時間的雙流線型工廠排程問題。此排程之研究目標為最小化寬裕時間之變異係數,寬裕時間即為交期與完工時間之間的差距。於此問題中,我們將需要相同整備治具的工件集合稱之為工件族。大多數以往的文獻中,不是使用family-based(將全部皆為同ㄧ家族的工件視為單一工件做排程),就是使用individual-based(每個工件排程是獨立地,而不考慮加入相同工件族)。本研究提出了group-based的方法(亦即將一個工件族區分成多個工件集合,排程中將每個工作集合當作單一個體)。此三個以基因演算法為基礎的GA-EDD-Family、GA-EDD-Group及GA-EDD-Individual方法被發展以及經由多種實驗做比較。實驗結果指出GA-EDD-Group的方法在多數情境下勝過於其他兩種方法。zh_TW
dc.description.abstractThis research examines a dual flow shop scheduling problem, which is in the context of considering cross-plant processing and setup times. The scheduling objective is to minimize coefficient of variation of slack times, in which the slack time of a job denotes the difference between the due date and its total processing time. Herein, a set of jobs that need the same setup is called a job family. Most prior literature either used a family-based approach (all jobs of a particular family are scheduled as a single job) or used an individual-based approach (each job is independently scheduled without considering its affiliation to its job family). This research proposes a group-based approach (that is, dividing a job family into several job groups, and scheduling each job group as a single entity). Several genetic algorithms (GAs), which are of GA-EDD-Family, GA-EDD-Group, or GA-EDD-Individual, have been developed and compared by numerical experiments. Experiment results indicate that the group-based approach outperforms the other two approaches in most scenarios.en_US
dc.language.isozh_TWen_US
dc.subject排程zh_TW
dc.subject跨廠zh_TW
dc.subject雙流線型生產zh_TW
dc.subject工件族zh_TW
dc.subject整備時間zh_TW
dc.subject交期zh_TW
dc.subject基因演算法zh_TW
dc.subjectschedulingen_US
dc.subjectcross-planten_US
dc.subjectdual flow shopen_US
dc.subjectfamilyen_US
dc.subjectsetup timeen_US
dc.subjectdue dateen_US
dc.subjectgenetic algorithm(GA)en_US
dc.title考慮工件族整備時間之雙流線型工廠排程zh_TW
dc.titleDual Flow Shops Scheduling with Family Setup Timesen_US
dc.typeThesisen_US
dc.contributor.department工業工程與管理學系zh_TW
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