Stochastic modeling and optimization of manufacturing systems and supply chains
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書誌事項
Stochastic modeling and optimization of manufacturing systems and supply chains
（International series in operations research & management science, 63）
Kluwer Academic, c2003
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注記
This volume originates from two workshops, Eindhoven University of Technology, April 24 - 26, 2001 and Cornell University, June 15, 2002
Includes bibliographical references and index
内容説明・目次
内容説明
This volume originates from two workshops, both focusing on themes that are reflected in the title of the volume. The first workshop took place at Eindhoven University of Technology, April 24-26, 2001, on the occasion of the University granting a doctorate honoris causa to Profes sor John A. Buzacott. The second workshop was held on June 15, 2002 at Cornell University (preceding the annual INFORMSjMSOM Confer ence), honoring John's retirement and his lifetime contributions. Each of the two workshops consisted of about a dozen technical presentations. The objective of the volume, however, is not to simply publish the proceedings of the two workshops. Rather, our objective is to put to gether a select set of articles, each organized into a well-written chapter, focusing on a timely topic. Collected into a single volume, these chapters aim to serve as a useful reference for researchers and practitioners alike, and also as reading materials for graduate courses or seminars.
目次
- Preface. 1: A Tribute to John A. Buzacott
- W.H.M. Zijm. 2: Publications of John A. Buzacott. 3: Evolution of Manufacturing System Models
- J.A. Buzacott. 3.1. Introduction. 3.2. Machine Interference. 3.3. Transfer Lines and Automated Flow Lines. 3.4. Job Shops and Flexible Manufacturing Systems. 3.5. Work Flow Control. 3.6. Structure and Organization of Manufacturing Systems. 3.7. People in Manufacturing. 3.8. Conclusions. 4: Reflections on Stochastic Manufacturing Models for Planning Decisions
- N.J. Vandaele, M.R. Lambrecht. 4.1. The Planning/Scheduling Conflict and its Remedies. 4.2. I-CLIPS: An Example of a Stochastic Model of a Manufacturing System. 4.3. Conclusions. 4.4. Appendix. 5: Two-Moment Approximations for Fork/Join Stations
- A. Krishnamurthy, R. Sun, M. Vernon. 5.1. Motivation. 5.2. Background. 5.3. Insights from Exact Analysis. 5.4. General Form of the Two-Moment Approximations. 5.5. Detailed Approximations and their Accuracy. 5.6. A Numerical Example. 5.7. Conclusions and Extensions. 5.8. Appendix. 6: Asymptotic Optimal Control of Queues with Feedback
- C.H. Xia, J.G. Shanthikumar. 6.1. Introduction. 6.2. Multi-class Queueing with Feedback. 6.3. Optimal Control for M/G/1 Queues. 6.4. Asymptotic Optimality for G/G/1 Queues with Feedback. 6.5. An Example: Brownian Limit May Not Give Strongly Asymptotically Optimal Solutions. 7: Multi-Echelon, Multi-Indenture Spare Parts Systems
- J.W. Rustenburg, G.-J. van Houtum, W.H.M. Zijm. 7.1. Introduction. 7.2. Modeling general spare parts support systems. 7.3. Exact Analysis. 7.4. An approximate evaluation procedure. 7.5. Field tests at the Royal Netherlands Navy. 7.6. Conclusion. 8: Substitutable Inventory: Single- and Multi-Period Models
- D.D. Yao, Shaohui Zheng. 8.1. Model Description. 8.2. The Optimal Substitution Policy. 8.3. The Optimal Replenishment Policy. 8.4. Multi-Period Problems. 8.5. Bibliographical Notes. 8.6. Appendix. 9: Evaluation and Optimization Of Strongly Ideal ATO Systems
- T.C. de Kok. 9.1. Introduction. 9.2. Analysis of an ATO System. 9.3. Computational Analysis of a Strongly Ideal ATO system. 9.4. Validation. 9.5. Optimal Base Stock Control of ATO Systems. 9.6. Summary and Conclusions. 10: Production/Inventory Control with Advance Demand Information
- F. Karaesmen, G. Liberopoulos, Y. Dallery. 10.1. Introduction. 10.2. Literature Review. 10.3. Single Stage Systems with Advance Demand Information. 10.4. Multi-Stage Systems with Advance Demand Information. 10.5. Conclusions. 11: Multi-Stage Control with Lot Sizing and Advance Demand Information
- G. Liberopoulos, I. Tsikis. 11.1. Introduction. 11.2. Modelling Assumptions. 11.3.
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