PROCESS SYSTEMS ENGINEERING - SUPPLY-CHAIN OPTIMIZATION V 4

Inspired by the leading authority in the field, the Centre for Process Systems Engineering at Imperial College London, this book includes theoretical developments, algorithms, methodologies and tools in process systems engineering and applications from the chemical, energy, molecular, biomedical and other areas. It spans a whole range of length scales seen in manufacturing industries, from molecular and nanoscale phenomena to enterprise-wide optimization and control. As such, this will appeal to a broad readership, since the topic applies not only to all technical processes but also due to the interdisciplinary expertise required to solve the challenge.
The ultimate reference work for years to come.

Lazaros G. Papageorgiou is a reader in the Department of Chemical Engineering at University College London (UCL). He received his Diploma in Chemical Engineering from the National technical University of Athens and a PhD in Chemical Engineering from Imperial College. Before joining UCL, he was adjunct Assistant Professor in the Department of Production Engineering and management at the technical University of Crete, and Research Associate at the centre for Process Systems Engineering (CPSE). He is author of over 90 publications in international journals and refereed conference proceedings.
Michael C. Georgiadis is a senior researcher in the centre for Process Systems Engineering at Imperial College London and the manger of academic business development of Process Systems Enterprise (PSE) Limited in Thessaloniki, Greece. He holds a first degree in University of Thessaloniki and a MSc and PhD from Imperial College. He has authored / co-authored over 40 journal publications and two books and has a long experience in the management and participation of more than 20 collaborative research contracts and projects.

Preface - Volume 4: Supply Chain Optimization.
List of Authors.
1. Supply Chains of High-Value Low-Volume Products (R. Sousa, N. Shah and L. G. Papageorgiou).
1.1 Introduction.
1.2 Literature on Supply-Chain Modeling and Optimization.
1.3 Stochastic Models.
1.4 Solution Algorithms.
1.5 Summary.
2. Solving Multiple Vehicle Pickup and Delivery Problems in Multisite Systems by a Rigorous Optimization Approach (R. Dondo, C.A. Méndez, J. Cerdá).
2.1 Introduction.
2.2 The Problem Definition.
2.3 The Problem Mathematical Formulation.
2.4 Time Window-Based Variable and Constraint Elimination Rules.
2.5 Numerical Results and Discussion.
2.6 Conclusions.
3. A Real Time Approximate Dynamic Programming Approach: A High Dimensional Supply Chain Application (N. E. Pratikakis, M. J. Realff, H. Lee).
3.1 Introduction.
3.2 Dynamic Programming.
3.3 A High-Dimensional Supply Chain Case Study.
3.4 Formulating the Problems as an MDP.
3.5 A Real-Time Approximate Dynamic Programming Algorithm.
3.6 Simulation Results.
3.7 Conclusions.
4. Robust Supply-Chain Operations through Rescheduling (A. Adhitya, R. Srinivasan, I.A. Karimi).
4.1 Introduction.
4.2 Refinery Supply Chain.
4.3 Rescheduling Problem Statement.
4.4 Rescheduling Methodologies.
4.5 Case Study.
4.6 Discussions.
5. Supply Chain Tactical Optimization in the Fruit Industry (G. L. Masini, A. M. Blanco, N. Petracci, J. A. Bandoni)
5.1 Introduction.
5.2 Literature Review.
5.3 Fruit Industry Supply Chain Description.
5.4 Mathematical Programming Model.
5.5 Results and Discussion.
5.6 Conclusions and Future Work.
6. Short-term Scheduling of Batch and Continuous Processes (M. A. Shaik, Ch. A. Floudas).
6.1 Classification of Scheduling Formulations.
6.2 Short-Term Scheduling of Batch Processes.
6.3 Short-Term Scheduling of Continuous Processes.
6.4 Conclusions.
7. Modeling and Optimization of Refinery Operations Considering Uncertainty (Z. Jia, M. G. Ierapetritou).
7.1 Introduction.
7.2 Refinery Scheduling.
7.3 Uncertainty Analysis.
7.4 Case Studies.
7.5 Summary and Future Work.
8. Production and Inventory Planning for Stock Preparation in the Tissue Paper Industry (J. Westerlund, M. Hästbacka, J. Kaplin, T. Westerlund).
8.1 Introduction.
8.2 Mathematical Programming as a Tool for Production Optimization.
8.3 Metsä Tissue Mänttä Mill.
8.4 The MISPT Architecture.
8.5 The Mixed-Time MILP Model.
8.6 Illustrative Case Examples.
8.7 Discussion.
9. Production Planning in Process Systems Engineering (C. Sung, C. T. Maravelias).
9.1 Introduction.
9.2 Background.
9.3 Integration of Production Planning and Scheduling.
9.4 Applications and Extensions.
9.5 Conclusions.
10. The Supply Chain as a Dynamical System (K. R. Jillson, E. J. Dozal-Mejorada, B.E. Yastie).
10.1 Introduction.
10.2 Literature Review.
10.3 Problem Formulation.
10.4 Inventory Control.
10.5 Assembly, Disassembly, and Packaging.
10.6 Flow Control and Local Balancing.
10.7 Summary and Conclusions.
Index.