Handbook of constraint programming
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...
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| Main Authors: | , , |
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| Format: | eBook Book |
| Language: | English |
| Published: |
Amsterdam ; Tokyo
Elsevier
2006
Elsevier Science & Technology Elsevier Science |
| Edition: | 1 |
| Series: | Foundations of artificial intelligence |
| Subjects: | |
| ISBN: | 9780444527264, 0444527265 |
| Online Access: | Get full text |
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Table of Contents:
- 7.3 Trading Time and Space by Hybrids of Search and Inference -- 7.4 Structure-Based Tractability in Search -- 7.5 Summary and Bibliographical Notes -- Chapter 8 The Complexity of Constraint Languages -- 8.1 Basic Definitions -- 8.2 Examples of Constraint Languages -- 8.3 Developing an Algebraic Theory -- 8.4 Applications of the Algebraic Theory -- 8.5 Constraint Languages Over an Infinite Set -- 8.6 Multi-Sorted Constraint Languages -- 8.7 Alternative Approaches -- 8.8 Future Directions -- Chapter 9 Soft Constraints -- 9.1 Background: Classical Constraints -- 9.2 Specific Frameworks -- 9.3 Generic Frameworks -- 9.4 Relations among Soft Constraint Frameworks -- 9.5 Search -- 9.6 Inference -- 9.7 Combining Search and Inference -- 9.8 Using Soft Constraints -- 9.9 Promising Directions for Further Research -- Chapter 10 Symmetry in Constraint Programming -- 10.1 Symmetries and Group Theory -- 10.2 Definitions -- 10.3 Reformulation -- 10.4 Adding Constraints Before Search -- 10.5 Dynamic Symmetry Breaking Methods -- 10.6 Combinations of Symmetry Breaking Methods -- 10.7 Successful Applications -- 10.8 Symmetry Expression and Detection -- 10.9 Further Research Themes -- 10.10 Conclusions -- Chapter 11 Modelling -- 11.1 Preliminaries -- 11.2 Representing a Problem -- 11.3 Propagation and Search -- 11.4 Viewpoints -- 11.5 Expressing the Constraints -- 11.6 Auxiliary Variables -- 11.7 Implied Constraints -- 11.8 Reformulations of CSPs -- 11.9 Combining Viewpoints -- 11.10 Symmetry and Modelling -- 11.11 Optimization Problems -- 11.12 Supporting Modelling and Reformulation -- Part II: Extensions, Languages, and Applications -- Chapter 12 Constraint Logic Programming -- 12.1 History of CLP -- 12.2 Semantics of Constraint Logic Programs -- 12.3 CLP for Conceptual Modeling -- 12.4 CLP for Design Modeling -- 12.5 Search in CLP -- 12.6 Impact of CLP
- Front Cover -- Title Page -- Copyright Page -- Foreword -- Editors -- Contributors -- Table of Contents -- Part I: Foundations -- Chapter 1 Introduction -- 1.1 Purpose of the Handbook -- 1.2 Structure and Content -- 1.3 Future Research -- Chapter 2 Constraint Satisfaction: An Emerging Paradigm -- 2.1 The Early Days -- 2.2 The Constraint Satisfaction Problem: Representation and Reasoning -- 2.3 Conclusions -- Chapter 3 Constraint Propagation -- 3.1 Background -- 3.2 Formal Viewpoint -- 3.3 Arc Consistency -- 3.4 Higher Order Consistencies -- 3.5 Domain-Based Consistencies Stronger than AC -- 3.6 Domain-Based Consistencies Weaker than AC -- 3.7 Constraint Propagation as Iteration of Reduction Rules -- 3.8 Specific Constraints -- Chapter 4 Backtracking Search Algorithms -- 4.1 Preliminaries -- 4.2 Branching Strategies -- 4.3 Constraint Propagation -- 4.4 Nogood Recording -- 4.5 Non-Chronological Backtracking -- 4.6 Heuristics for Backtracking Algorithms -- 4.7 Randomization and Restart Strategies -- 4.8 Best-First Search -- 4.9 Optimization -- 4.10 Comparing Backtracking Algorithms -- Chapter 5 Local Search Methods -- 5.1 Introduction -- 5.2 Randomised Iterative Improvement Algorithms -- 5.3 Tabu Search and Related Algorithms -- 5.4 Penalty-Based Local Search Algorithms -- 5.5 Other Approaches -- 5.6 Local Search for Constraint Optimisation Problems -- 5.7 Frameworks and Toolkits for Local Search -- 5.8 Conclusions and Outlook -- Chapter 6 Global Constraints -- 6.1 Notation and Preliminaries -- 6.2 Examples of Global Constraints -- 6.3 Complete Filtering Algorithms -- 6.4 Optimization Constraints -- 6.5 Partial Filtering Algorithms -- 6.6 Global Variables -- 6.7 Conclusion -- Chapter 7 Tractable Structures for Constraint Satisfaction Problems -- 7.1 Background -- 7.2 Structure-Based Tractability in Inference
- 18.3 Random Problems with Structure -- 18.4 Runtime Variability -- 18.5 History -- 18.6 Conclusions -- Chapter 19 Temporal CSPs -- 19.1 Preliminaries -- 19.2 Constraint-Based Formalisms for Reasoning About Time -- 19.3 Efficient Algorithms for Temporal CSPs -- 19.4 More Expressive Queries for Temporal CSPs -- 19.5 First-Order Temporal Constraint Languages -- 19.6 The Scheme of Indefinite Constraint Databases -- 19.7 Conclusions -- Chapter 20 Distributed Constraint Programming -- 20.1 Definitions -- 20.2 Distributed Search -- 20.3 Improvements and Variants -- 20.4 Distributed Local Search -- 20.5 Open Constraint Programming -- 20.6 Further Issues -- 20.7 Conclusion -- Chapter 21 Uncertainty and Change -- 21.1 Background and Definitions -- 21.2 Example: Course Scheduling -- 21.3 Uncertain Problems -- 21.4 Problems that Change -- 21.5 Pseudo-dynamic Formalisms -- 21.6 Challenges and Future Trends -- 21.7 Summary -- Chapter 22 Constraint-Based Scheduling and Planning -- 22.1 Constraint Programming Models for Scheduling -- 22.2 Constraint Programming Models for Planning -- 22.3 Constraint Propagation for Resource Constraints -- 22.4 Constraint Propagation on Optimization Criteria -- 22.5 Heuristic Search -- 22.6 Conclusions -- Chapter 23 Vehicle Routing -- 23.1 The Vehicle Routing Problem -- 23.2 Operations Research Approaches -- 23.3 Constraint Programming Approaches -- 23.4 Constraint Programming in Search -- 23.5 Using Constraint Programming as a Subproblem Solver -- 23.6 CP-VRP in the Real World -- 23.7 Conclusions -- Chapter 24 Configuration -- 24.1 What Is Configuration? -- 24.2 Configuration Knowledge -- 24.3 Constraint Models for Configuration -- 24.4 Problem Solving for Configuration -- 24.5 Conclusion -- Chapter 25 Constraint Applications in Networks -- 25.1 Electricity Networks -- 25.2 Water (Oil) Networks -- 25.3 Data Networks
- 12.7 Future of CLP and Interesting Research Questions -- Chapter 13 Constraints in Procedural and Concurrent Languages -- 13.1 Procedural and Object-Oriented Languages -- 13.2 Concurrent Constraint Programming -- 13.3 Rule-Based Languages -- 13.4 Challenges and Opportunities -- 13.5 Conclusion -- Chapter 14 Finite Domain Constraint Programming Systems -- 14.1 Architecture for Constraint Programming Systems -- 14.2 Implementing Constraint Propagation -- 14.3 Implementing Search -- 14.4 Systems Overview -- 14.5 Outlook -- Chapter 15 Operations Research Methods in Constraint Programming -- 15.1 Schemes for Incorporating OR into CP -- 15.2 Plan of the Chapter -- 15.3 Linear Programming -- 15.4 Mixed Integer/Linear Modeling -- 15.5 Cutting Planes -- 15.6 Relaxation of Global Constraints -- 15.7 Relaxation of Piecewise Linear and Disjunctive Constraints -- 15.8 Lagrangean Relaxation -- 15.9 Dynamic Programming -- 15.10 Branch-and-Price Methods -- 15.11 Benders Decomposition -- 15.12 Toward Integration of CP and OR -- Chapter 16 Continuous and Interval Constraints -- 16.1 From Discrete to Continuous Constraints -- 16.2 The Branch-and-Reduce Framework -- 16.3 Consistency Techniques -- 16.4 Numerical Operators -- 16.5 Hybrid Techniques -- 16.6 First Order Constraints -- 16.7 Applications and Software packages -- 16.8 Conclusion -- Chapter 17 Constraints over Structured Domains -- 17.1 History and Applications -- 17.2 Constraints over Regular and Constructed Sets -- 17.3 Constraints over Finite Set Intervals -- 17.4 Influential Extensions to Subset Bound Solvers -- 17.5 Constraints over Maps, Relations and Graphs -- 17.6 Constraints over Lattices and Hierarchical Trees -- 17.7 Implementation Aspects -- 17.8 Applications -- 17.9 Further Topics -- Chapter 18 Randomness and Structure -- 18.1 Random Constraint Satisfaction -- 18.2 Random Satisfiability
- 25.4 Conclusion -- Chapter 26 Bioinformatics and Constraints -- 26.1 What Biologists Want from Bioinformatics -- 26.2 The Central Dogma -- 26.3 A Classification of Problem Areas -- 26.4 Sequence Related Problems -- 26.5 Structure Related Problems -- 26.6 Function Related Problems -- 26.7 Microarrays -- Index