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題名 數個瓶頸為基礎的啟發式法則求解彈性流程系統排程問題
BOTTLENECK-BASED HEURISTICS FOR FLEXIBLE FLOW LINE SCHEDULING PROBLEMS WITH A BOTTLENECK STAGE作者 陳俊龍
Chen,Chun Lung貢獻者 陳春龍
Chen,Chuen Lung
陳俊龍
Chen,Chun Lung關鍵詞 瓶頸
彈性流程系統
非等效平行機
派工法則
啟發式方法日期 2006 上傳時間 18-Sep-2009 14:34:20 (UTC+8) 摘要 In this research, we study flexible flow line scheduling problems with unrelated parallel machines and with a bottleneck stage. The measures of performances are to minimize makespan, to minimize the number of tardy jobs, and to minimize total tardiness, considered respectively. Several bottleneck-based heuristics are developed to solve these scheduling problems. A bottleneck-driven multiple insertion heuristic (BDMIH) is proposed to solve problems with makespan as the objective. The essential idea of BDMIH is that we think the scheduling of jobs at the bottleneck stage may affect the performance of a heuristic for scheduling jobs in all stages. Therefore, in this heuristic we let jobs entering the sequence at the first stage be driven by their sequence entering at the bottleneck stage. Given an FFL problem with a bottleneck stage, this heuristic first identifies the bottleneck stage, then generates an initial sequence of jobs by a variant of Johnson’s rule (SPT-LPT rule), and finally applies a multiple insertion heuristic to find the best schedule. Another heuristic, a bottleneck-based due-date decision heuristic (BBDDDH), is developed to solve problems with the number of tardy jobs as the objective. The heuristic consists of three steps: (1) Identifying the bottleneck stage, (2) Scheduling jobs at the bottleneck stage and the upstream stages ahead of the bottleneck stage, and (3) Using dispatching rules to schedule jobs at the downstream stages behind the bottleneck stage. A new approach is developed to find the arrival times of the jobs at the bottleneck stage, and two decision rules are developed to schedule jobs at bottleneck stage. This new approach neatly overcomes the difficulty of determining feasible arrival times of jobs at bottleneck stage. The last bottleneck-based heuristic, a bottleneck-driven adaptable multiple insertion heuristic (BDAMIH), is constructed to solve problems with total tardiness as the objective. The main idea of BDAMIH is combined with the ideas of BDMIH and BBDDDH. The main difference between BDAMIH and BDMIH is that BDMIH generates an initial sequence of jobs before performing the insertion heuristic; however, BDAMIH is adaptable to select a job within the process of the insertion heuristic. To evaluate the performance of the proposed heuristics, several well-known dispatching rules and heuristics are investigated for comparison purposes and computational experiments are performed on randomly generated test problems. Computational results show that the proposed heuristics significantly outperform all well-known dispatching rules or heuristics. Also, an analysis of the experimental factors is performed, and several interesting insights of the proposed heuristics are discovered. 參考文獻 Adler, L., Fraiman, N., Kobacker, E., Pinedo, M., Plotnicoff, J. C., and Wu, T. P., BPSS: A scheduling support system for the packaging industry. Operations Research. 1993, 41, 641–648.
Agnetis, A., Pacifici, A., Rossi, F., Lucertini, M., Nicoletti, S., Nicolo, F., Oriolo, G., Pacciarelli, D., and Pesaro, E., Scheduling of flexible flow shop in an automobile assembly plant. European Journal of Operational Research, 1997, 97, 348–362.
Alisantoso, D., Khoo, L. P. and Jiang, P. Y., An immune algorithm approach to the scheduling of a flexible PCB flow shop. International Journal of Advanced Manufacturing Technology, 2003, 22, 819–827.
Azizoglu, M., Cakmak, E. and Kondakci, S., A flexible flowshop problem with total flow time minimization. European Journal of Operational Research, 2001, 132, 528–538.
Baker, K. R. and Bertrand, J. W., A dynamic priority rule for scheduling against due-dates. Journal of Operations Management, 1982, 3, 37–42.
Baker, K. R. and Kanet, J. J., Job shop scheduling with modified due-dates. Journal of Operations Management, 1983, 4, 11–22.
Bertel, S. and Billaut, J. C., A genetic algorithm for an industrial multiprocessor flow shop scheduling problem with recirculation. European Journal of Operational Research, 2004, 159, 651–662.
Brah, S. A., A comparative analysis of due date based job sequencing rules in a flow shop with multiple processors. Production Planning and Control, 1996, 7, 362–373.
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Brah, S. A. and Wheeler, G. E., Comparison of scheduling rules in a flow shop with multiple processors: A simulation, Simulation, 1998, 71, 302–311.
Campbell, H. G., Dudek, R. A. and Smith, M. L., A heuristic algorithm for the n-job, m-machine sequencing problem. Management Science, 1970, 16, 630–637.
Chen, C. L., Usher, J. M., and Palanimuthu, N., A tabu search based heuristic for a flexible flow line with minimum flow time criterion. International Journal of Industrial Engineering, 1998, 5, 157–168.
Chen, Y. C. and Lee, C. E., Bottleneck-based group scheduling in a flow line cell. International Journal of Industrial Engineering-Applications and Practice, 1998, 5, 288–300.
Choi, S. W., Kim, Y. D. and Lee, G. C., Minimizing total tardiness of orders with reentrant lots in a hybrid flowshop. International Journal of Production Research, 2005, 43, 2149–2167.
Conway, R., Comments on an exposition of multiple constraint scheduling. Production and Operations Management, 1997, 6, 23–24.
Dannenbring, D. G., An evaluation of flow shop sequencing heuristics. Management Science, 1977, 23, 1174–1182.
Du, J. and Leung, J. Y., Minimizing total tardiness on one machine is NP-hard. Mathematics of Operations Research, 1990, 15, 483–495.
Feaminan, J. M., Gupta, J. N. D. and Leisten, R., A review and classification of heuristics for permutation flow-shop scheduling with makespan objective. Journal of the Operational Research Society, 2004, 55, 1243–1255.
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國立政治大學
資訊管理研究所
90356502
95資料來源 http://thesis.lib.nccu.edu.tw/record/#G0903565021 資料類型 thesis dc.contributor.advisor 陳春龍 zh_TW dc.contributor.advisor Chen,Chuen Lung en_US dc.contributor.author (Authors) 陳俊龍 zh_TW dc.contributor.author (Authors) Chen,Chun Lung en_US dc.creator (作者) 陳俊龍 zh_TW dc.creator (作者) Chen,Chun Lung en_US dc.date (日期) 2006 en_US dc.date.accessioned 18-Sep-2009 14:34:20 (UTC+8) - dc.date.available 18-Sep-2009 14:34:20 (UTC+8) - dc.date.issued (上傳時間) 18-Sep-2009 14:34:20 (UTC+8) - dc.identifier (Other Identifiers) G0903565021 en_US dc.identifier.uri (URI) https://nccur.lib.nccu.edu.tw/handle/140.119/35258 - dc.description (描述) 博士 zh_TW dc.description (描述) 國立政治大學 zh_TW dc.description (描述) 資訊管理研究所 zh_TW dc.description (描述) 90356502 zh_TW dc.description (描述) 95 zh_TW dc.description.abstract (摘要) In this research, we study flexible flow line scheduling problems with unrelated parallel machines and with a bottleneck stage. The measures of performances are to minimize makespan, to minimize the number of tardy jobs, and to minimize total tardiness, considered respectively. Several bottleneck-based heuristics are developed to solve these scheduling problems. A bottleneck-driven multiple insertion heuristic (BDMIH) is proposed to solve problems with makespan as the objective. The essential idea of BDMIH is that we think the scheduling of jobs at the bottleneck stage may affect the performance of a heuristic for scheduling jobs in all stages. Therefore, in this heuristic we let jobs entering the sequence at the first stage be driven by their sequence entering at the bottleneck stage. Given an FFL problem with a bottleneck stage, this heuristic first identifies the bottleneck stage, then generates an initial sequence of jobs by a variant of Johnson’s rule (SPT-LPT rule), and finally applies a multiple insertion heuristic to find the best schedule. Another heuristic, a bottleneck-based due-date decision heuristic (BBDDDH), is developed to solve problems with the number of tardy jobs as the objective. The heuristic consists of three steps: (1) Identifying the bottleneck stage, (2) Scheduling jobs at the bottleneck stage and the upstream stages ahead of the bottleneck stage, and (3) Using dispatching rules to schedule jobs at the downstream stages behind the bottleneck stage. A new approach is developed to find the arrival times of the jobs at the bottleneck stage, and two decision rules are developed to schedule jobs at bottleneck stage. This new approach neatly overcomes the difficulty of determining feasible arrival times of jobs at bottleneck stage. The last bottleneck-based heuristic, a bottleneck-driven adaptable multiple insertion heuristic (BDAMIH), is constructed to solve problems with total tardiness as the objective. The main idea of BDAMIH is combined with the ideas of BDMIH and BBDDDH. The main difference between BDAMIH and BDMIH is that BDMIH generates an initial sequence of jobs before performing the insertion heuristic; however, BDAMIH is adaptable to select a job within the process of the insertion heuristic. To evaluate the performance of the proposed heuristics, several well-known dispatching rules and heuristics are investigated for comparison purposes and computational experiments are performed on randomly generated test problems. Computational results show that the proposed heuristics significantly outperform all well-known dispatching rules or heuristics. Also, an analysis of the experimental factors is performed, and several interesting insights of the proposed heuristics are discovered. en_US dc.description.tableofcontents LIST OF TABLES ivLIST OF FIGURES viiLIST OF ABBREVIATIONS viiiCHAPTER 1INTRODUCTION 11.1 Introduction 11.2 Objective of the Study 5CHAPTRR 2LITERATURE REVIEW 72.1 The Classification of Approaches for FFL Scheduling Problems 72.2 Heuristics for FFL Problems with Identical Parallel Machines 112.3 Heuristics for FFL Problems with Unrelated Parallel Machines 152.4 Summary 16CHAPTER 3HEURISTICS FOR FLEXIBLE FLOW LINE SCHEDULING PROBLEMS 173.1 Nations and Assumptions 183.1.1 Nations 183.1.2 Assumptions 193.2 Proposed Heuristics to Minimize Makespan 203.2.1 Bottleneck-Driven Multiple Insertion Heuristic (BDMIH) 213.3 Proposed Heuristics to Minimize Number of Tardy Jobs 253.3.1 Bottleneck-Based Due Date Decision Heuristic (BBDDDH) 253.4 Proposed Heuristics to Minimize Total Tardiness 323.4.1 Bottleneck-Driven Adaptable Multiple Insertion Heuristic (BDAMIH) 33CHAPTER 4COMPUTATIONAL EXPERIMENTS 364.1 Conducting an Experiment for Minimizing Makespan Problems 414.1.1 Conducting an Experiment for Minimizing Makespan Problems in Unrelated Parallel Machine Environments 414.1.2 Conducting an Experiment for Minimizing Makespan Problems in Identical Parallel Machine Environments 504.2 Conducting an Experiment for Minimizing the Number of Tardy Job Problems 544.2.1 Conducting an Experiment for Minimizing the Number of Tardy Job Problems in Unrelated Parallel Machine Environments 544.2.2 Conducting an Experiment for Minimizing the Number of Tardy Job Problems in Identical Parallel Machine Environments 654.3 Conducting an Experiment for Minimizing Total Tardiness Problems 704.3.1 Conducting an Experiment for Minimizing Total Tardiness Problems in Unrelated Parallel Machine Environments 714.3.2 Conducting an Experiment for Minimizing Total Tardiness Problems in Identical Parallel Machine Environments 80CHAPTER 5CONCLUSIONS 85REFERENCES 90 LIST OF TABLESTABLESTABLE 4.1 Experimental Design for Generating Minimizing Makespan Test Problems 39TABLE 4.2 Experimental Design for Generating Minimizing the Number of Tardy Jobs and Total Tardiness Test Problems 40TABLE 4.1.1.1 Performance Comparisons of the Proposed Heuristics and the Dispatching Rules (in terms of average RPD, average makespan (AM), and number of best solutions (NBS)) 45TABLE 4.1.1.2 Analysis of Variance to Test the Significance of the Machine Selection Rules 46TABLE 4.1.1.3 Results of LSD Test for Machine Selection Rules 46TABLE 4.1.1.4 Analysis of Variance to Test the Significance of the Algorithms when ECALLM Is Used 47TABLE 4.1.1.5 Results of LSD Test for Bottleneck-based Heuristics 48TABLE 4.1.1.6 Effect of the Experimental Factors on the BDMIH/ECALLM (in terms of average RPD) 48TABLE 4.1.1.7 Average Computational Time Required for the Heuristics 48TABLE 4.1.2.1 Performance Comparisons of the Proposed Heuristics and the Dispatching Rules (in terms of average RPD, average makespan(AM), and number of best solutions (NBS)) 53TABLE 4.1.2.2 Analysis of Variance to Test the Significance of the Algorithms 53TABLE 4.1.2.3 Results of LSD Test for Bottleneck-based Heuristics 53TABLE 4.1.2.4 Effect of the Experimental Factors on the BDMIH (in terms of average RPD) 54TABLE 4.2.1.1 Performance Comparisons of the Proposed Heuristics and the Dispatching Rules (in terms of average RDI, average number of total tardy jobs (ATJ), and number of best solutions (NBS)) 59TABLE 4.2.1.2 Analysis of Variance to Test the Significance of the Machine Selection Rules 59TABLE 4.2.1.3 Results of LSD Test for Machine Selection Rules 59TABLE 4.2.1.4 Analysis of Variance to Test the Significance of the Algorithms when ECALLM Is Used 60TABLE 4.2.1.5 Results of LSD Test for Bottleneck-based Heuristics 60TABLE 4.2.1.6 Effect of the Experimental Factors on the BODD+ATC/ECALLM (in terms of average RDI) 64TABLE 4.2.1.7 Average Computational Time Required for the Heuristics 65TABLE 4.2.2.1 Performance Comparisons of the Proposed Heuristics and the Dispatching Rules (in terms of average RDI, average number of total tardy jobs (ATJ), and number of best solutions (NBS)) 67TABLE 4.2.2.2 Analysis of Variance to Test the Significance of the Algorithms 67TABLE 4.2.2.3 Results of LSD Test for Bottleneck-based Heuristics 69TABLE 4.2.2.4 Effect of the Experimental Factors on the BODD (in terms of average RDI) 69TABLE 4.3.1.1 Performance Comparisons of the Proposed heuristics, the Dispatching Rules, and the SMIH (in terms of average RDI, average total tardiness (ATT), and number of best solutions (NBS)) 73TABLE 4.3.1.2 Analysis of Variance to Test the Significance of the Machine Selection Rules 73TABLE 4.3.1.3 Results of LSD Test for Machine Selection Rules 74TABLE 4.3.1.4 Analysis of Variance to Test the Significance of the Algorithms when ECALLM Is Used 74TABLE 4.3.1.5 Results of LSD Test for Bottleneck-based Heuristics 74TABLE 4.3.1.6 Effect of the Experimental Factors on the BDAMIH/ECALLM (in terms of average RDI) 77TABLE 4.3.1.7 Average Computational Time Required for the Heuristics 79TABLE 4.3.2.1 Performance Comparisons of the Proposed Heuristics and the Dispatching Rules (in terms of average RDI, average total tardiness (ATT), and number of best solutions (NBS)) 83TABLE 4.3.2.2 Analysis of Variance to Test the Significance of the Algorithms 83TABLE 4.3.2.3 Results of LSD Test for Bottleneck-based Heuristics 84TABLE 4.3.2.4 Effect of the Experimental Factors on the BDAMIH (in terms of average RDI) 84 LIST OF FIGURESFIGURESFIGURE 1.1 An example of a flexible flow line 2FIGURE 1.2 Overview of the taxonomy 9 zh_TW dc.format.extent 46510 bytes - dc.format.extent 30981 bytes - dc.format.extent 38256 bytes - dc.format.extent 27589 bytes - dc.format.extent 38373 bytes - dc.format.extent 108197 bytes - dc.format.extent 199182 bytes - dc.format.extent 23972 bytes - dc.format.extent 44328 bytes - dc.format.mimetype application/pdf - dc.format.mimetype application/pdf - dc.format.mimetype application/pdf - dc.format.mimetype application/pdf - dc.format.mimetype application/pdf - dc.format.mimetype application/pdf - dc.format.mimetype application/pdf - dc.format.mimetype application/pdf - dc.format.mimetype application/pdf - dc.language.iso en_US - dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0903565021 en_US dc.subject (關鍵詞) 瓶頸 zh_TW dc.subject (關鍵詞) 彈性流程系統 zh_TW dc.subject (關鍵詞) 非等效平行機 zh_TW dc.subject (關鍵詞) 派工法則 zh_TW dc.subject (關鍵詞) 啟發式方法 zh_TW dc.title (題名) 數個瓶頸為基礎的啟發式法則求解彈性流程系統排程問題 zh_TW dc.title (題名) BOTTLENECK-BASED HEURISTICS FOR FLEXIBLE FLOW LINE SCHEDULING PROBLEMS WITH A BOTTLENECK STAGE en_US dc.type (資料類型) thesis en dc.relation.reference (參考文獻) Adler, L., Fraiman, N., Kobacker, E., Pinedo, M., Plotnicoff, J. C., and Wu, T. P., BPSS: A scheduling support system for the packaging industry. Operations Research. 1993, 41, 641–648. zh_TW dc.relation.reference (參考文獻) Agnetis, A., Pacifici, A., Rossi, F., Lucertini, M., Nicoletti, S., Nicolo, F., Oriolo, G., Pacciarelli, D., and Pesaro, E., Scheduling of flexible flow shop in an automobile assembly plant. European Journal of Operational Research, 1997, 97, 348–362. zh_TW dc.relation.reference (參考文獻) Alisantoso, D., Khoo, L. P. and Jiang, P. Y., An immune algorithm approach to the scheduling of a flexible PCB flow shop. International Journal of Advanced Manufacturing Technology, 2003, 22, 819–827. zh_TW dc.relation.reference (參考文獻) Azizoglu, M., Cakmak, E. and Kondakci, S., A flexible flowshop problem with total flow time minimization. European Journal of Operational Research, 2001, 132, 528–538. zh_TW dc.relation.reference (參考文獻) Baker, K. R. and Bertrand, J. W., A dynamic priority rule for scheduling against due-dates. Journal of Operations Management, 1982, 3, 37–42. zh_TW dc.relation.reference (參考文獻) Baker, K. R. and Kanet, J. J., Job shop scheduling with modified due-dates. Journal of Operations Management, 1983, 4, 11–22. zh_TW dc.relation.reference (參考文獻) Bertel, S. and Billaut, J. C., A genetic algorithm for an industrial multiprocessor flow shop scheduling problem with recirculation. European Journal of Operational Research, 2004, 159, 651–662. zh_TW dc.relation.reference (參考文獻) Brah, S. A., A comparative analysis of due date based job sequencing rules in a flow shop with multiple processors. Production Planning and Control, 1996, 7, 362–373. zh_TW dc.relation.reference (參考文獻) Brah, S. A. and Loo, L. L., Heuristics for scheduling in a flow shop with multiple processors. European Journal of Operational Research, 1999, 113, 113–122. zh_TW dc.relation.reference (參考文獻) Brah, S. A. and Wheeler, G. E., Comparison of scheduling rules in a flow shop with multiple processors: A simulation, Simulation, 1998, 71, 302–311. zh_TW dc.relation.reference (參考文獻) Campbell, H. G., Dudek, R. A. and Smith, M. L., A heuristic algorithm for the n-job, m-machine sequencing problem. Management Science, 1970, 16, 630–637. zh_TW dc.relation.reference (參考文獻) Chen, C. L., Usher, J. M., and Palanimuthu, N., A tabu search based heuristic for a flexible flow line with minimum flow time criterion. International Journal of Industrial Engineering, 1998, 5, 157–168. zh_TW dc.relation.reference (參考文獻) Chen, Y. C. and Lee, C. E., Bottleneck-based group scheduling in a flow line cell. International Journal of Industrial Engineering-Applications and Practice, 1998, 5, 288–300. zh_TW dc.relation.reference (參考文獻) Choi, S. W., Kim, Y. D. and Lee, G. C., Minimizing total tardiness of orders with reentrant lots in a hybrid flowshop. 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