Principles and Practice of Constraint Programming -

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Editeur : Springer International Publishing Ag

Langue : Anglais

Parution : 01/08/2018

Format : Moyen, de 350g à 1kg

Nombre de pages : 792

Expédition : 1177

Dimensions : 23.5 x 15.5 x 43.0

ISBN : 3319983334

Résumé :
This book constitutes the proceedings of the 24th International Conference on Principles and Practice of Constraint Programming, CP 2018, held in Lille, France, in August 2018.

The 41 full and 9 short papers presented in this volume were carefully reviewed and selected from 114 submissions. They deal with all aspects of computing with constraints including theory, algorithms, environments, languages, models, systems, and applications such as decision making, resource allocation, scheduling, configuration, and planning. The papers were organized according to the following topics/tracks: main technical track; applications track; CP and data science; CP and music; CP and operations research; CP, optimization and power system management; multiagent and parallel CP; and testing and verification.

Sommaire:
Main Technical Track.- Automatic Discovery and Exploitation of Promising Subproblems for Tabulation.- Propagating regular membership with dashed strings.- A Constraint-based Encoding for Domain-Independent Temporal Planning.- Decremental Consistency Checking of Temporal Constraints: Algorithms for the Point Algebra and the ORD-Horn Class.- Domain Reduction for Valued Constraints by Generalising Methods from CSP.- Solver-independent Large Neighbourhood Search.- Solution-Based Phase Saving for CP: A Value-Selection Heuristic to Simulate Local Search Behavior in Complete Solvers.- An SMT Approach to Fractional Hypertree Width.- On the non-Degeneracy of Unsatisfiability Proof Graphs produced by SAT Solvers.- Sequential Precede Chain for value symmetry elimination.- An Incremental SAT-Based Approach to Reason Efficiently On Qualitative Constraint Network.- Clause Learning and New Bounds for Graph Coloring.- Portfolio-based algorithm selection for circuit QBFs.- Making Compact-Table Compact.- Approximation Strategies for Incomplete MaxSAT.- A novel graph-based heuristic approach for solving sport scheduling problem.- Augmenting Stream Constraint Programming with Eventuality Conditions.- A Complete Tolerant Algebraic Side-Channel Attack for AES with CP.- Evaluating QBF Solvers: Quantifier Alternations Matter.- The Quantified Valued Constraint Satisfaction Problem.- MLIC: A MaxSAT-Based framework for learning interpretable classification rules.- Objective as a Feature for Robust Search Strategies.- PW-ACBit: Extending Compact-Table to Enforce Pairwise Consistency on Table Constraints.- Automatic Generation and Selection of Streamlined Constraint Models via Monte Carlo Search on a Model Lattice.- Efficient Methods for Constraint Acquisition.- A Circuit Consellmanntraint for Multiple Tours Problems.- Towards Semi-Automatic Learning-based Model Transformation.- Finding solutions by finding inconsistencies.- The Effect of Structural Measures and Merges on SAT Solver Performance.- Learning-Sensitive Backdoors with Restarts.- Applications Track.- Process Plant Layout Optimization: Equipment Allocation.- A Constraint Programming Approach for Solving Patient Transportation Problems.- Unifying Reserve Design Strategies with Graph Theory and Constraint Programming.- Self-Configuring Cost-Sensitive Hierarchical Clustering With Recourse.- CP and Data Science Track.- User's constraints in itemset mining.- On Maximal Frequent Itemsets Mining With Constraints.- A Parallel SAT based Framework for Closed Frequent Itemsets Mining.- Effective Deep Learning for Constraint Satisfaction Problems.- CP and Music Track.- Extending the Capacity of 1/f Noise Generation.- CP and Operations Research Track.- Securely and Automatically Deploying Micro-Services in an Hybrid Cloud Infrastructure.- Improving Energetic Propagations for Cumulative Scheduling.- CP, Optimization, and Power System Management Track.- A Fast and Scalable Algorithm for Scheduling Large Numbers of Devices under Real-Time Pricing.- Multiagent and Parallel CP Track.- Balancing Asymmetry in Max-sum using Split Constraint Factor Graphs.- A Large Neighboring Search Schema for Multi-Agent Optimization.- Distributed constrained search by selfish agents for efficient equilibria.- Testing and Verification Track.- Metamorphic Testing of Constraint Solvers.- Algebraic Fault Attack on SHA Hash Functions using Programmatic SAT Solvers....