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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
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dc.contributor.advisor | 黃奎隆 | zh_TW |
dc.contributor.advisor | Kwei-Long Huang | en |
dc.contributor.author | 姚莉紅 | zh_TW |
dc.contributor.author | Li-Hong Yao | en |
dc.date.accessioned | 2023-08-15T16:29:36Z | - |
dc.date.available | 2023-11-09 | - |
dc.date.copyright | 2023-08-15 | - |
dc.date.issued | 2023 | - |
dc.date.submitted | 2023-07-28 | - |
dc.identifier.citation | Arroyo, J. E. C., Leung, J. Y. T., & Tavares, R. G. (2019). An iterated greedy algorithm for total flow time minimization in unrelated parallel batch machines with unequal job release times. Engineering Applications of Artificial Intelligence, 77, 239-254. https://doi.org/10.1016/j.engappai.2018.10.012
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A meta-heuristic to minimize makespan for parallel batch machines with arbitrary job sizes. European Journal of Operational Research, 240(3), 649-665. https://doi.org/10.1016/j.ejor.2014.07.039 Joo, B. J., Choi, Y. C., & Xirouchakis, P. (2013). Dispatching rule-based algorithms for a dynamic flexible flow shop scheduling problem with time-dependent process defect rate and quality feedback. Procedia CIRP, 7, 163-168. Lee, C.-Y., Uzsoy, R., & Martin-Vega, L. A. (1992). Efficient algorithms for scheduling semiconductor burn-in operations. Operations Research, 40(4), 764-775. Lei, D., & Guo, X. P. (2011). Variable neighbourhood search for minimising tardiness objectives on flow shop with batch processing machines. International Journal of Production Research, 49(2), 519-529. https://doi.org/10.1080/00207540903536130 Lei, D., & Wang, T. (2011). An effective neighborhood search algorithm for scheduling a flow shop of batch processing machines. 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A three-stage assembly flow shop scheduling problem with blocking and sequence-dependent set up times. Journal of Industrial Engineering International, 8(1), 26. https://doi.org/10.1186/2251-712X-8-26 Pinedo, M. L. (2012). Scheduling (Vol. 29). Springer. Ruiz, R., & Vázquez-Rodríguez, J. A. (2010). The hybrid flow shop scheduling problem. European Journal of Operational Research, 205(1), 1-18. Shen, L., Gupta, J. N. D., & Buscher, U. (2014). Flow shop batching and scheduling with sequence-dependent setup times. Journal of Scheduling, 17(4), 353-370. https://doi.org/10.1007/s10951-014-0369-x Tan, Y., Mönch, L., & Fowler, J. W. (2018). A hybrid scheduling approach for a two-stage flexible flow shop with batch processing machines. Journal of Scheduling, 21(2), 209-226. https://doi.org/10.1007/s10951-017-0530-4 Tewari, A. A. (2012). Minimizing total weighted tardiness in a two staged flexible flow-shop with batch processing, incompatible job families and unequal ready times using time window decomposition. Arizona State University. Tyagi, N., Varshney, R., & Chandramouli, A. (2013). A Comprehensive Study of Genetic Algorithm for the Flowshop Scheduling Problem. International Journal Of Scientific & Engineering Research, 4(9), 2447-2458. Uzsoy, R. (1994). Scheduling a single batch processing machine with non-identical job sizes. The International Journal of Production Research, 32(7), 1615-1635. Wang, S., Kurz, M., Mason, S. J., & Rashidi, E. (2019). Two-stage hybrid flow shop batching and lot streaming with variable sublots and sequence-dependent setups. International Journal of Production Research, 57(22), 6893-6907. https://doi.org/10.1080/00207543.2019.1571251 Xiao, X., Ji, B., Yu, S. S., & Wu, G. (2023). A tabu-based adaptive large neighborhood search for scheduling unrelated parallel batch processing machines with non-identical job sizes and dynamic job arrivals. Flexible Services and Manufacturing Journal. https://doi.org/10.1007/s10696-023-09488-9 Xiong, F., Xing, K., Wang, F., Lei, H., & Han, L. (2014). Minimizing the total completion time in a distributed two stage assembly system with setup times. Computers & Operations Research, 47, 92-105. Zhou, S., Liu, M., Chen, H., & Li, X. (2016). An effective discrete differential evolution algorithm for scheduling uniform parallel batch processing machines with non-identical capacities and arbitrary job sizes. International Journal of Production Economics, 179, 1-11. https://doi.org/10.1016/j.ijpe.2016.05.014 | - |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/88480 | - |
dc.description.abstract | 在實際生產製造環境中,因為需將許多的變數及不確定性同時納入考慮,因此當今企業便透過導入功能更具彈性的機台以因應製造生產環境的發展與變化,藉由納入批量生產的特性至新型機台中以提升製程的生產效率。但新型機台及既有機台並行使用的現象將會因為機台特性的差異而對生產排程有重大的影響,因此若能將具批量生產的新機台及單一生產的舊機台同時考量至生產排程規劃,將可使排程結果更貼近於實際生產現場排程狀況。
本研究以混合流線型生產排程問題為基礎,探討如何將工件建構成批量的形式,並考量各批量間的加工順序,在新舊機台具備的加工容量不一致之條件下,讓多種工件在同一機台可同時進行加工,以減少工件的完工時間,期望能達成交期限制。另外研究中亦納入獨立與相依設置時間、產品種類及製程型態等因素,以更符合實際製造現場,建構出能考量實務中包含的條件限制且在有限資源下使效益最大化地發揮的一套生產排程計劃,於客戶給定的交期期限內提供足夠的產能及產出量,以減少排程計畫與實際生產狀況的偏差。不僅如此,面對製造業在生產技術上的快速發展,需將求解生產排程結果的時間上限也一併列入考慮,以及時求得最適排程計畫,避免因求解時間過長造成訂單交期的延遲。本研究將探討以最小化總延遲時間為目標,求解具有批量生產機台之兩階段混合流線型生產排程問題,並以混合整數線性規劃模型與基因演算法的建構,求解一套完整的排程計畫,以順應製造環境中競爭且多變的特性。 | zh_TW |
dc.description.abstract | In the actual manufacturing environment, since many variables and uncertainties need to be taken into consideration at the same time, companies introduced machines with more flexible functions to cope with the development of the manufacturing environment nowadays, and incorporating more production characteristics into new machines to improve the production efficiency of the whole manufacturing operation. However, the coexistence of new machines and old machines will have a significant impact on production scheduling due to differences in machine characteristics. Therefore, if new machines with batch processing and old machines with single processing can be considered to the production scheduling at the same time, the results will be closer to the actual production environment.
Based on the hybrid flowshop scheduling problem, this research discusses how to construct jobs into batches, and considers batch sequence, so that multiple jobs can be processed simultaneously on the same machine to reduce the completion time of jobs, and finally meet the deadlines of jobs. In addition, other factors such as independent and dependent setup time, product types, and process recipes are also included in this research, so as to be more in line with the actual manufacturing environment, and then to construct a production scheduling plan which not only considers the conditions in the practical operations and maximize profits under limited resources, but also provides sufficient production capacity and satisfying the due date given by the customers and reduce the deviation between the scheduling plan and the actual production environment. Furthermore, in the face of the rapid development of production technology in the manufacturing industry, the computing time must also be taken into consideration, so as to obtain the optimal or close-to-optimal solutions in a reasonable time and avoid tardiness of jobs. This research will propose the solving method of the two-stage hybrid flow shop scheduling problem with batch production machines with the objective of minimizing the total tardiness time, and obtain a complete scheduling plan by constructing a mixed integer linear programming model and genetic algorithm, to accommodate the competitive and changing nature of the manufacturing environment. | en |
dc.description.provenance | Submitted by admin ntu (admin@lib.ntu.edu.tw) on 2023-08-15T16:29:36Z No. of bitstreams: 0 | en |
dc.description.provenance | Made available in DSpace on 2023-08-15T16:29:36Z (GMT). No. of bitstreams: 0 | en |
dc.description.tableofcontents | 口試委員審定書 i
摘要 ii Abstract iii 目錄 v 圖目錄 vii 表目錄 ix 第一章 緒論 1 1.1 研究背景與動機 1 1.2 研究目的與架構 3 第二章 文獻探討 5 2.1 混合流線型生產排程 5 2.2 批量生產 6 2.3 基因演算法 13 2.3.1 基因演算法架構 14 2.3.2 基因演算法流程說明 15 2.4 小結 20 第三章 問題描述與研究方法 21 3.1 問題描述 21 3.2 問題假設與限制 24 3.3 混合整數線性規劃模型 25 3.4 混合整數線性規劃模型小型範例應用 28 第四章 基因演算法 32 4.1 基因演算法之建構 32 4.1.1 批量派工法則概念說明 32 4.1.2 基因演算法步驟 40 4.2 基因演算法範例說明 41 第五章 數值分析及驗證 43 5.1 情境設計與參數設定說明 43 5.2 實驗結果與分析 54 5.3 實務案例驗證 62 5.3.1 實務案例介紹 62 5.3.2 實務案例排程結果 63 第六章 結論 65 6.1 結論 65 6.2 未來研究方向 66 參考文獻 68 附錄一 實務案例工件資訊參數 71 附錄二 實務案例機台資訊參數 73 | - |
dc.language.iso | zh_TW | - |
dc.title | 考量批量生產特性之兩階段混合流線型生產排程 | zh_TW |
dc.title | Two-Stage Hybrid Flowshop Scheduling with Consideration of Batch Processing | en |
dc.type | Thesis | - |
dc.date.schoolyear | 111-2 | - |
dc.description.degree | 碩士 | - |
dc.contributor.oralexamcommittee | 陳文智;楊朝龍 | zh_TW |
dc.contributor.oralexamcommittee | Wen-Chih Chen;Chao-Lung Yang | en |
dc.subject.keyword | 批量生產,兩階段混合流線型生產排程,混合整數線性規劃模型,基因演算法,最小化總延遲時間, | zh_TW |
dc.subject.keyword | Batch processing,Two-stage hybrid flowshop scheduling,Mixed integer linear programming model,Genetic algorithm,Minimize total tardiness, | en |
dc.relation.page | 73 | - |
dc.identifier.doi | 10.6342/NTU202302346 | - |
dc.rights.note | 同意授權(限校園內公開) | - |
dc.date.accepted | 2023-08-01 | - |
dc.contributor.author-college | 工學院 | - |
dc.contributor.author-dept | 工業工程學研究所 | - |
顯示於系所單位: | 工業工程學研究所 |
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