Integration of Constraint Programming, Artificial Intelligence, and Operations Research: 19th International Conference, CPAIOR 2022, Los Angeles, CA, USA, June 20-23, 2022, Proceedings

Author:   Pierre Schaus
Publisher:   Springer International Publishing AG
Edition:   1st ed. 2022
Volume:   13292
ISBN:  

9783031080104


Pages:   442
Publication Date:   11 June 2022
Format:   Paperback
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

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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


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Overview

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”.

Full Product Details

Author:   Pierre Schaus
Publisher:   Springer International Publishing AG
Imprint:   Springer International Publishing AG
Edition:   1st ed. 2022
Volume:   13292
Weight:   0.706kg
ISBN:  

9783031080104


ISBN 10:   3031080106
Pages:   442
Publication Date:   11 June 2022
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Table of 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.

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