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Principles and Practice of Constraint Programming

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Cover of 'Principles and Practice of Constraint Programming'

Table of Contents

  1. Altmetric Badge
    Book Overview
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    Chapter 1 Dashed Strings and the Replace(-all) Constraint
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    Chapter 2 Combinatorial Search in CP-Based Iterated Belief Propagation
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    Chapter 3 Replication-Guided Enumeration of Minimal Unsatisfiable Subsets
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    Chapter 4 Solving Satisfaction Problems Using Large-Neighbourhood Search
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    Chapter 5 Quantum-Accelerated Global Constraint Filtering
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    Chapter 6 Pure MaxSAT and Its Applications to Combinatorial Optimization via Linear Local Search
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    Chapter 7 Tractable Fragments of Temporal Sequences of Topological Information
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    Chapter 8 Strengthening Neighbourhood Substitution
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    Chapter 9 Effective Encodings of Constraint Programming Models to SMT
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    Chapter 10 Watched Propagation of $$0$$-$$1$$ Integer Linear Constraints
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    Chapter 11 Bounding Linear Programs by Constraint Propagation: Application to Max-SAT
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    Chapter 12 On Relation Between Constraint Propagation and Block-Coordinate Descent in Linear Programs
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    Chapter 13 DPMC: Weighted Model Counting by Dynamic Programming on Project-Join Trees
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    Chapter 14 Aggregation and Garbage Collection for Online Optimization
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    Chapter 15 Treewidth-Aware Quantifier Elimination and Expansion for QCSP
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    Chapter 16 A Time Leap Challenge for SAT-Solving
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    Chapter 17 Breaking Symmetries with RootClique and LexTopSort
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    Chapter 18 Towards Faster Reasoners by Using Transparent Huge Pages
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    Chapter 19 The Argmax Constraint
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    Chapter 20 Certifying Solvers for Clique and Maximum Common (Connected) Subgraph Problems
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    Chapter 21 Phase Transition Behavior in Knowledge Compilation
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    Chapter 22 A Faster Exact Algorithm to Count X3SAT Solutions
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    Chapter 23 Visualizations to Summarize Search Behavior
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    Chapter 24 Parallelization of TSP Solving in CP
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    Chapter 25 Using Resolution Proofs to Analyse CDCL Solvers
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    Chapter 26 Core-Guided Model Reformulation
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    Chapter 27 Filtering Rules for Flow Time Minimization in a Parallel Machine Scheduling Problem
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    Chapter 28 MaxSAT-Based Postprocessing for Treedepth
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    Chapter 29 Perturbing Branching Heuristics in Constraint Solving
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    Chapter 30 Finding the Hardest Formulas for Resolution
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    Chapter 31 HADDOCK: A Language and Architecture for Decision Diagram Compilation
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    Chapter 32 Towards a Generic Interval Solver for Differential-Algebraic CSP
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    Chapter 33 abstractXOR: A global constraint dedicated to differential cryptanalysis
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    Chapter 34 In Pursuit of an Efficient SAT Encoding for the Hamiltonian Cycle Problem
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    Chapter 35 Large Neighborhood Search for Temperature Control with Demand Response
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    Chapter 36 Solving the Group Cumulative Scheduling Problem with CPO and ACO
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    Chapter 37 A Branch-and-bound Algorithm to Rigorously Enclose the Round-Off Errors
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    Chapter 38 Leveraging Reinforcement Learning, Constraint Programming and Local Search: A Case Study in Car Manufacturing
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    Chapter 39 Computing the Local Aromaticity of Benzenoids Thanks to Constraint Programming
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    Chapter 40 Using Constraint Programming to Generate Benzenoid Structures in Theoretical Chemistry
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    Chapter 41 RobTest: A CP Approach to Generate Maximal Test Trajectories for Industrial Robots
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    Chapter 42 A Two-Phase Constraint Programming Model for Examination Timetabling at University College Cork
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    Chapter 43 Exact Approaches to the Multi-agent Collective Construction Problem
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    Chapter 44 The Confidence Constraint: A Step Towards Stochastic CP Solvers
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    Chapter 45 Parity (XOR) Reasoning for the Index Calculus Attack
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    Chapter 46 Constraint-Based Software Diversification for Efficient Mitigation of Code-Reuse Attacks
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    Chapter 47 Pushing Data into CP Models Using Graphical Model Learning and Solving
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    Chapter 48 Generating Random Logic Programs Using Constraint Programming
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    Chapter 49 Towards Formal Fairness in Machine Learning
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    Chapter 50 Verifying Equivalence Properties of Neural Networks with ReLU Activation Functions
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    Chapter 51 Learning the Satisfiability of Pseudo-Boolean Problem with Graph Neural Networks
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    Chapter 52 A Machine Learning Based Splitting Heuristic for Divide-and-Conquer Solvers
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    Chapter 53 Theoretical and Experimental Results for Planning with Learned Binarized Neural Network Transition Models
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    Chapter 54 Omissions in Constraint Acquisition
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    Chapter 55 Computing Optimal Decision Sets with SAT
Attention for Chapter 5: Quantum-Accelerated Global Constraint Filtering
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Chapter title
Quantum-Accelerated Global Constraint Filtering
Chapter number 5
Book title
Principles and Practice of Constraint Programming
Published by
Springer, Cham, September 2020
DOI 10.1007/978-3-030-58475-7_5
Book ISBNs
978-3-03-058474-0, 978-3-03-058475-7
Authors

Kyle E. C. Booth, Bryan O’Gorman, Jeffrey Marshall, Stuart Hadfield, Eleanor Rieffel, Booth, Kyle E. C., O’Gorman, Bryan, Marshall, Jeffrey, Hadfield, Stuart, Rieffel, Eleanor

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