Principles and Practice of Constraint Programming [[electronic resource] ] : 25th International Conference, CP 2019, Stamford, CT, USA, September 30 – October 4, 2019, Proceedings / / edited by Thomas Schiex, Simon de Givry |
Edizione | [1st ed. 2019.] |
Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
Descrizione fisica | 1 online resource (XXVI, 788 p. 831 illus., 179 illus. in color.) |
Disciplina | 005.11 |
Collana | Programming and Software Engineering |
Soggetto topico |
Mathematical logic
Computer science—Mathematics Artificial intelligence Software engineering Arithmetic and logic units, Computer Mathematical Logic and Formal Languages Mathematics of Computing Artificial Intelligence Software Engineering/Programming and Operating Systems Arithmetic and Logic Structures |
ISBN | 3-030-30048-X |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Technical Track -- Instance Generation via Generator Instances -- Automatic Detection of At-Most-One and Exactly-One Relations for Improved SAT Encodings of Pseudo-Boolean Constraints -- Exploring Declarative Local-Search Neighbourhoods with Constraint Programming -- Vehicle routing by learning from historical solutions -- On Symbolic Approaches for Computing the Matrix Permanent -- Towards the Characterization of Max-Resolution Transformations of UCSs by UP-Resilience -- Logic-Based Benders Decomposition for Super Solutions: an Application to the Kidney Exchange Problem -- Exploiting Glue Clauses to Design Effective CDCL Branching Heuristics -- Industrial Size Job-Shop Scheduling tackled by Present-Day CP Solvers -- Dual Hashing-based Algorithms for Discrete Integration -- Techniques Inspired by Local Search for Incomplete MaxSAT and the Linear Algorithm: Varying Resolution and Solution-Guided Search -- A Join-Based Hybrid Parameter for Constraint Satisfaction -- An Incremental SAT-Based Approach to the Graph Colouring Problem -- Constraint-based Techniques in Stochastic Local Search MaxSAT Solving -- Trimming Graphs Using Clausal Proof Optimization -- Improved Job Sequencing Bounds from Decision Diagrams -- Integration of structural constraints into TSP models -- Representing fitness landscapes by valued constraints to understand the complexity of local search -- Estimating the Number of Solutions of Cardinality Constraints through range and roots Decomposition -- Understanding the Empirical Hardness of Random Optimisation Problems -- Guarded Constraint Models Define Treewidth Preserving Reductions -- Automatic Streamlining for Constrained Optimisation -- Compiling Conditional Constraints -- Training Binarized Neural Networks using MIP and CP -- Application Track -- Models for Radiation Therapy Patient Scheduling -- Constraint Programming-based Job Dispatching for Modern HPC Applications -- Scheduling of Mobile Robots using Constraint Programming -- Decomposition and Cut Generation Strategies for Solving Multi-Robot Deployment Problems -- Multi-agent and Parallel CP Track -- An Improved GPU-based SAT Model Counter -- Reducing Bias in Preference Aggregation for Multiagent Soft Constraint Problems -- Testing and Verification Track -- A Cube Distribution Approach to QBF Solving and Certificate Minimization -- Functional Synthesis with Examples -- SolverCheck: Declarative Testing of Constraints -- Encodings for Enumeration-Based Program Synthesis -- Lemma Synthesis for Automating Induction over Algebraic Data Types -- CP and Data Science Track -- Modeling Pattern Set Mining using Boolean Circuits -- Differential Privacy of Hierarchical Census Data: An Optimization Approach -- Generic Constraint-based Block Modeling using Constraint Programming -- Reward Potentials for Planning with Learned Neural Network Transition Models -- Exploiting Counterfactuals for Scalable Stochastic Optimization -- Structure-driven Multiple Constraint Acquisition -- Computational Sustainability Track -- Towards robust scenarios of spatio-temporal renewable energy planning: A GIS-RO approach -- Peak-hour Rail Demand Shifting with Discrete Optimisation -- CP and Life Sciences Track -- Functional significance checking in noisy gene regulatory networks. |
Record Nr. | UNISA-996466445803316 |
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. di Salerno | ||
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Principles and Practice of Constraint Programming : 25th International Conference, CP 2019, Stamford, CT, USA, September 30 – October 4, 2019, Proceedings / / edited by Thomas Schiex, Simon de Givry |
Edizione | [1st ed. 2019.] |
Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
Descrizione fisica | 1 online resource (XXVI, 788 p. 831 illus., 179 illus. in color.) |
Disciplina |
005.11
005.131 |
Collana | Programming and Software Engineering |
Soggetto topico |
Mathematical logic
Computer science—Mathematics Artificial intelligence Software engineering Arithmetic and logic units, Computer Mathematical Logic and Formal Languages Mathematics of Computing Artificial Intelligence Software Engineering/Programming and Operating Systems Arithmetic and Logic Structures |
ISBN | 3-030-30048-X |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Technical Track -- Instance Generation via Generator Instances -- Automatic Detection of At-Most-One and Exactly-One Relations for Improved SAT Encodings of Pseudo-Boolean Constraints -- Exploring Declarative Local-Search Neighbourhoods with Constraint Programming -- Vehicle routing by learning from historical solutions -- On Symbolic Approaches for Computing the Matrix Permanent -- Towards the Characterization of Max-Resolution Transformations of UCSs by UP-Resilience -- Logic-Based Benders Decomposition for Super Solutions: an Application to the Kidney Exchange Problem -- Exploiting Glue Clauses to Design Effective CDCL Branching Heuristics -- Industrial Size Job-Shop Scheduling tackled by Present-Day CP Solvers -- Dual Hashing-based Algorithms for Discrete Integration -- Techniques Inspired by Local Search for Incomplete MaxSAT and the Linear Algorithm: Varying Resolution and Solution-Guided Search -- A Join-Based Hybrid Parameter for Constraint Satisfaction -- An Incremental SAT-Based Approach to the Graph Colouring Problem -- Constraint-based Techniques in Stochastic Local Search MaxSAT Solving -- Trimming Graphs Using Clausal Proof Optimization -- Improved Job Sequencing Bounds from Decision Diagrams -- Integration of structural constraints into TSP models -- Representing fitness landscapes by valued constraints to understand the complexity of local search -- Estimating the Number of Solutions of Cardinality Constraints through range and roots Decomposition -- Understanding the Empirical Hardness of Random Optimisation Problems -- Guarded Constraint Models Define Treewidth Preserving Reductions -- Automatic Streamlining for Constrained Optimisation -- Compiling Conditional Constraints -- Training Binarized Neural Networks using MIP and CP -- Application Track -- Models for Radiation Therapy Patient Scheduling -- Constraint Programming-based Job Dispatching for Modern HPC Applications -- Scheduling of Mobile Robots using Constraint Programming -- Decomposition and Cut Generation Strategies for Solving Multi-Robot Deployment Problems -- Multi-agent and Parallel CP Track -- An Improved GPU-based SAT Model Counter -- Reducing Bias in Preference Aggregation for Multiagent Soft Constraint Problems -- Testing and Verification Track -- A Cube Distribution Approach to QBF Solving and Certificate Minimization -- Functional Synthesis with Examples -- SolverCheck: Declarative Testing of Constraints -- Encodings for Enumeration-Based Program Synthesis -- Lemma Synthesis for Automating Induction over Algebraic Data Types -- CP and Data Science Track -- Modeling Pattern Set Mining using Boolean Circuits -- Differential Privacy of Hierarchical Census Data: An Optimization Approach -- Generic Constraint-based Block Modeling using Constraint Programming -- Reward Potentials for Planning with Learned Neural Network Transition Models -- Exploiting Counterfactuals for Scalable Stochastic Optimization -- Structure-driven Multiple Constraint Acquisition -- Computational Sustainability Track -- Towards robust scenarios of spatio-temporal renewable energy planning: A GIS-RO approach -- Peak-hour Rail Demand Shifting with Discrete Optimisation -- CP and Life Sciences Track -- Functional significance checking in noisy gene regulatory networks. |
Record Nr. | UNINA-9910349297703321 |
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
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