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dc.contributor.author張慕萱en_US
dc.contributor.authorChang, Mu-Hsuanen_US
dc.contributor.author巫木誠en_US
dc.contributor.authorWu, Muh-Cherngen_US
dc.date.accessioned2014-12-12T02:32:52Z-
dc.date.available2014-12-12T02:32:52Z-
dc.date.issued2012en_US
dc.identifier.urihttp://140.113.39.130/cdrfb3/record/nctu/#GT070053319en_US
dc.identifier.urihttp://hdl.handle.net/11536/71573-
dc.description.abstract本論文探討議題為具維修特性之分散且彈性零工式排程問題。此排程問題的複雜度為NP-hard,包含四項子決策,分別為 (1) 工件指派,(2) 作業指派,(3)作業排序,(4) 維修決策。本論文發展兩個啟發式演算法搭配一新解表達(簡稱Sjob-1t)來求解此排程問題。Sjob-1t為工件及虛擬維修工件的排序,意即一個染色體就是一個特定的工件排序(a particular sequence of jobs)。並且發展四種啟發式演算法(heuristic methods)求解具維修特性之分散且彈性零工式排程問題的四項子決策。本研究是以全域最大完工時間(global makespan)為目標函數,實驗結果顯示本研究所提出的兩個演算法在多數例題中,績效優於文獻所發展的演算法。zh_TW
dc.description.abstractThis thesis aims at solve the problem of distributed flexible job-shop subject to preventive maintenance (i.e., the DFJSP/PM problem). This scheduling problem is NP-hard, which contains four sub-decisions: (1) job-to-cell assignment, (2) operation-to-machine, (3) operation sequencing, and (4) preventive maintenance assignment. To solve this scheduling problem, this thesis develops two meta-heuristic algorithms based on a new solution representation (called Sjob-1t). Sjob-1t represents a solution by a sequence of generic jobs, which is composed of normal jobs and virtual PM jobs. Four heuristic rules are developed to decode the sequence of generic jobs to obtain the aforementioned four sub-decisions. The scheduling objecive is global makespan. Experiment results show that the two proposed algorithms both outperform prior algorithms in solving the DFJSP/PM problem.en_US
dc.language.isozh_TWen_US
dc.subject分散且彈性零工式生產排程zh_TW
dc.subject蟻群最佳化演算法zh_TW
dc.subject基因演算法zh_TW
dc.subject解表達法zh_TW
dc.subject預先維修zh_TW
dc.subjectDistributed flexible job-shopen_US
dc.subjectAnt colony algorithmen_US
dc.subjectGenetic algorithmen_US
dc.subjectSolution representationen_US
dc.subjectPrevent maintenanceen_US
dc.title以工件序一元基因染色體表達法求解具維修特性之DFJSP排程問題zh_TW
dc.titleUsing job-based chromosomes with 1-tuple genes to develop meta-heuristic algorithms for DFJSP scheduling subject to maintenanceen_US
dc.typeThesisen_US
dc.contributor.department工業工程與管理系所zh_TW
Appears in Collections:Thesis