Perspectives in supply chain risk management

Facility location and supply chain management - A review

Constraint programming is a powerful paradigm for solving combinatorial search problems that draws on a wide range of techniques from artificial intelligence, computer science, databases, programming languages, and operations research. Constraint programming is currently applied with success to many domains, such as scheduling, planning, vehicle routing, configuration, networks, and bioinformatics.

The aim of this handbook is to capture the full breadth and depth of the constraint programming field and to be encyclopedic in its scope and coverage. While there are several excellent books on constraint programming, such books necessarily focus on the main notions and techniques and cannot cover also extensions, applications, and languages. The handbook gives a reasonably complete coverage of all these lines of work, based on constraint programming, so that a reader can have a rather precise idea of the whole field and its potential. Of course each line of work is dealt with in a survey-like style, where some details may be neglected in favor of coverage. However, the extensive bibliography of each chapter will help the interested readers to find suitable sources for the missing details. Each chapter of the handbook is intended to be a self-contained survey of a topic, and is written by one or more authors who are leading researchers in the area.

The intended audience of the handbook is researchers, graduate students, higher-year undergraduates and practitioners who wish to learn about the state-of-the-art in constraint programming. No prior knowledge about the field is necessary to be able to read the chapters and gather useful knowledge. Researchers from other fields should find in this handbook an effective way to learn about constraint programming and to possibly use some of the constraint programming concepts and techniques in their work, thus providing a means for a fruitful cross-fertilization among different research areas.

The handbook is organized in two parts. The first part covers the basic foundations of constraint programming, including the history, the notion of constraint propagation, basic search methods, global constraints, tractability and computational complexity, and important issues in modeling a problem as a constraint problem. The second part covers constraint languages and solver, several useful extensions to the basic framework (such as interval constraints, structured domains, and distributed CSPs), and successful application areas for constraint programming.

- Covers the whole field of constraint programming
- Survey-style chapters
- Five chapters on applications

Table of Contents

Foreword (Ugo Montanari) 
Part I : Foundations
Chapter 1. Introduction (Francesca Rossi, Peter van Beek, Toby Walsh) 
Chapter 2. Constraint Satisfaction: An Emerging Paradigm (Eugene C. Freuder, Alan K. Mackworth) 
Chapter 3. Constraint Propagation (Christian Bessiere) 
Chapter 4. Backtracking Search Algorithms (Peter van Beek) 
Chapter 5. Local Search Methods (Holger H. Hoos, Edward Tsang) 
Chapter 6. Global Constraints (Willem-Jan van Hoeve, Irit Katriel)
Chapter 7. Tractable Structures for CSPs (Rina Dechter)
Chapter 8. The Complexity of Constraint Languages
(David Cohen, Peter Jeavons) 
Chapter 9. Soft Constraints (Pedro Meseguer, Francesca Rossi, Thomas Schiex) 
Chapter 10. Symmetry in Constraint Programming
(Ian P. Gent, Karen E. Petrie, Jean-Francois Puget)
Chapter 11. Modelling (Barbara M. Smith) 
Part II : Extensions, Languages, and Applications

Chapter 12. Constraint Logic Programming (Kim Marriott, Peter J. Stuckey, Mark Wallace) 
Chapter 13. Constraints in Procedural and Concurrent Languages (Thom Fruehwirth, Laurent Michel, Christian Schulte)
Chapter 14. Finite Domain Constraint Programming Systems (Christian Schulte, Mats Carlsson) 
Chapter 15. Operations Research Methods in Constraint Programming (John Hooker) 
Chapter 16. Continuous and Interval Constraints(Frederic Benhamou, Laurent Granvilliers) 
Chapter 17. Constraints over Structured Domains
(Carmen Gervet) 
Chapter 18. Randomness and Structure (Carla Gomes, Toby Walsh)
Chapter 19. Temporal CSPs (Manolis Koubarakis)
Chapter 20. Distributed Constraint Programming
(Boi Faltings) 
Chapter 21. Uncertainty and Change (Kenneth N. Brown, Ian Miguel)
Chapter 22. Constraint-Based Scheduling and Planning
(Philippe Baptiste, Philippe Laborie, Claude Le Pape, Wim Nuijten)
Chapter 23. Vehicle Routing (Philip Kilby, Paul Shaw) 
Chapter 24. Configuration (Ulrich Junker)
Chapter 25. Constraint Applications in Networks
(Helmut Simonis)
Chapter 26. Bioinformatics and Constraints (Rolf Backofen, David Gilbert)

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Handbook of Constraint Programming

Recent trends in modeling of deteriorating inventory

Information systems in supply chain integration and management

The power of information technology can be harnessed to help supply chain members establish partnerships for better supply chain system performance. Supply chain partnerships can mitigate deficiencies associated with decentralized control and reduce the “bullwhip effect”. This study illustrates the benefits of supply chain partnerships based on information sharing. For a decentralized supply chain comprising a manufacturer and a retailer, we derive the members’ optimal inventory policies under different information sharing scenarios. We show that increasing information sharing among the members in a decentralized supply chain will lead to Pareto improvement in the performance of the entire chain. Specifically, the supply chain members can reap benefits in terms of reductions in inventory levels and cost savings from forming partnerships with one another. A case study is provided for illustration.

Benefits of information sharing with supply chain partnerships

A strategic model for supply chain design with logical constraints: formulation and solution

Network DEA model for supply chain performance evaluation

DEA models for resource reallocation and production input/output estimation

Purpose – Although a lot of attention has been paid to demand information sharing in the recent decade, few studies look at the value of supply information sharing. The purpose of this paper is to address the importance of timely supply information sharing to the supply chain management under disruption is addressed.Design/methodology/approach – By introducing a Directed Acyclic Supply Network (DASN) model and an Impact Network (INet) model, the impact of a disruption on the performance of the supply chain is quantified. A comprehensive algorithm is developed to calculate the time and cost impact of the disruption. Insights about the value of timely supply information sharing are further discussed, based on quantitative relationships of material flows. Finally, an application of the above model in a main manufacturer of China is introduced. It is then compared to its performance in the case of timely supply information sharing with cases where information is not shared or is shared late.Findings – By time...

Hong Yan

Papers

Benefits of information sharing with supply chain partnerships

A strategic model for supply chain design with logical constraints: formulation and solution

Network DEA model for supply chain performance evaluation

DEA models for resource reallocation and production input/output estimation

Enhancing agility by timely sharing of supply information