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Integration of Constraint Programming, Artificial Intelligence, and Operations Research : 19th International Conference, CPAIOR 2022, Los Angeles, CA, USA, June 20-23, 2022, Proceedings / edited by Pierre Schaus.
- Format:
- Book
- Series:
- Computer Science (SpringerNature-11645)
- Lecture notes in computer science 1611-3349 ; 13292
- Lecture Notes in Computer Science, 1611-3349 ; 13292
- Language:
- English
- Subjects (All):
- Computer science-Mathematics.
- Artificial intelligence.
- Computer science.
- Computer engineering.
- Computer networks.
- Mathematics of Computing.
- Artificial Intelligence.
- Theory of Computation.
- Computer Engineering and Networks.
- Local Subjects:
- Mathematics of Computing.
- Artificial Intelligence.
- Theory of Computation.
- Computer Engineering and Networks.
- Physical Description:
- 1 online resource (XIX, 442 pages) : 101 illustrations, 64 illustrations in color.
- Edition:
- 1st ed. 2022.
- Contained In:
- Springer Nature eBook
- Place of Publication:
- Cham : Springer International Publishing : Imprint: Springer, 2022.
- System Details:
- text file PDF
- Summary:
- This book constitutes the proceedings of the 19th International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research, CPAIOR 2022, which was held in Los Angeles, CA, USA, in June 2022.The 28 regular papers presented were carefully reviewed and selected from a total of 60 submissions. The conference program included a Master Class on the topic "Bridging the Gap between Machine Learning and Optimization".
- Contents:
- A Two-Phase Hybrid Approach for the Hybrid Flexible Flowshop with Transportation Times
- A SAT Encoding to compute Aperiodic Tiling Rhythmic Canons
- Transferring Information across Restarts in MIP
- Towards Copeland Optimization in Combinatorial Problems
- Coupling Different Integer Encodings for SAT
- Model-Based Algorithm Configuration with Adaptive Capping and Prior Distributions
- Shattering Inequalities for Learning Optimal Decision Trees
- Learning Pseudo-Backdoors for Mixed Integer Programs
- Leveraging Integer Linear Programming to Learn Optimal Fair Rule Lists
- Solving the Job Shop Scheduling Problem extended with AGVs - Classical and Quantum Approaches
- Stochastic Decision Diagrams
- Improving the robustness of EPS to solve the TSP
- Efficient operations between MDDs and constraints
- Deep Policy Dynamic Programming for Vehicle Routing Problems
- Learning a Propagation Complete Formula
- A FastMap-Based Algorithm for Block Modeling
- Packing by Scheduling: Using Constraint Programming to Solve a Complex 2D Cutting Stock Problem
- Dealing with the product constraint
- Multiple-choice knapsack constraint in graphical models
- A Learning Large Neighborhood Search for the Staff Rerostering Problem
- Practically Uniform Solution Sampling in Constraint Programming
- Training Thinner and Deeper Neural Networks: Jumpstart Regularization
- Hybrid Offline/Online Optimization for Energy Management via Reinforcement Learning
- Enumerated Types and Type Extensions for MiniZinc
- A parallel algorithm for generalized arc-consistent filtering for the Alldifferent constraint
- Analyzing the Reachability Problem in Choice Networks
- Model-based Approaches to Multi-Attribute Diverse Matching.
- Other Format:
- Printed edition:
- ISBN:
- 978-3-031-08011-1
- 9783031080111
- Access Restriction:
- Restricted for use by site license.
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