Integration of AI and OR Techniques in Constraint Programming: 12th International Conference, CPAIOR 2015, Barcelona, Spain, May 18-22, 2015, Proceedings - Tapa blanda

Sinopsis

A Time-Dependent No-Overlap Constraint: Application to Urban Delivery Problems.- Rectangle Placement for VLSI Testing.- A Constraint-Based Local Search for Edge Disjoint Rooted Distance-Constrained Minimum Spanning Tree Problem.- A Benders Approach to the Minimum Chordal Completion Problem.- MaxSAT-Based Scheduling of B2B Meetings.- Embedding Decision Trees and Random Forests in Constraint Programming.- Scheduling with Fixed Maintenance, Shared Resources and Nonlinear Feedrate Constraints: A Mine Planning Case Study.- Learning Value Heuristics for Constraint Programming.- Derivative-Free Optimization: Lifting Single-Objective to Multi-Objective Algorithm.- Branching on Multi-aggregated Variables.- Time-Table Disjunctive Reasoning for the Cumulative Constraint.- Uncertain Data Dependency Constraints in Matrix Models.- An Efficient Local Search for Partial Latin Square Extension Problem.- Enhancing MIP Branching Decisions by Using the Sample Variance of Pseudo Costs.- BDD-Guided Clause Generation.- Combining Constraint Propagation and Discrete Ellipsoid-Based Search to Solve the Exact Quadratic Knapsack Problem.- Large Neighborhood Search for Energy Aware Meeting Scheduling in Smart Buildings.- ILP and CP Formulations for the Lazy Bureaucrat Problem.- The Smart Table Constraint.- Constraint-Based Sequence Mining Using Constraint Programming.- A Comparative Study of MIP and CP Formulations for the B2B Scheduling Optimization Problem.- Constraint-Based Local Search for Golomb Rulers.- Packing While Traveling: Mixed Integer Programming for a Class of Nonlinear Knapsack Problems.- MaxSAT-Based Cutting Planes for Learning Graphical Models.- A Multistage Stochastic Programming Approach to the Dynamic and Stochastic VRPTW.- Constraint Solving on Bounded String Variables.- Freight Train Threading with Different Algorithms.- Learning General Constraints in CSP.- Understanding the Potential of Propagators.- Failure-Directed Search for Constraint-Based Scheduling.

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