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Integration of AI and OR Techniques in Constraint Programming

Overview of attention for book
Cover of 'Integration of AI and OR Techniques in Constraint Programming'

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 1 Sharpening Constraint Programming Approaches for Bit-Vector Theory
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    Chapter 2 Range-Consistent Forbidden Regions of Allen’s Relations
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    Chapter 3 MDDs are Efficient Modeling Tools: An Application to Some Statistical Constraints
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    Chapter 4 On Finding the Optimal BDD Relaxation
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    Chapter 5 Design and Implementation of Bounded-Length Sequence Variables
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    Chapter 6 In Search of Balance: The Challenge of Generating Balanced Latin Rectangles
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    Chapter 7 Debugging Unsatisfiable Constraint Models
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    Chapter 8 Learning Decision Trees with Flexible Constraints and Objectives Using Integer Optimization
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    Chapter 9 Relaxation Methods for Constrained Matrix Factorization Problems: Solving the Phase Mapping Problem in Materials Discovery
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    Chapter 10 Minimizing Landscape Resistance for Habitat Conservation
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    Chapter 11 A Hybrid Approach for Stator Winding Design Optimization
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    Chapter 12 A Distributed Optimization Method for the Geographically Distributed Data Centres Problem
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    Chapter 13 Explanation-Based Weighted Degree
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    Chapter 14 Counting Weighted Spanning Trees to Solve Constrained Minimum Spanning Tree Problems
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    Chapter 15 The Weighted Arborescence Constraint
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    Chapter 16 Learning When to Use a Decomposition
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    Chapter 17 Experiments with Conflict Analysis in Mixed Integer Programming
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    Chapter 18 A First Look at Picking Dual Variables for Maximizing Reduced Cost Fixing
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    Chapter 19 Experimental Validation of Volume-Based Comparison for Double-McCormick Relaxations
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    Chapter 20 Minimum Makespan Vehicle Routing Problem with Compatibility Constraints
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    Chapter 21 Solving the Traveling Salesman Problem with Time Windows Through Dynamically Generated Time-Expanded Networks
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    Chapter 22 A Fast Prize-Collecting Steiner Forest Algorithm for Functional Analyses in Biological Networks
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    Chapter 23 Scenario-Based Learning for Stochastic Combinatorial Optimisation
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    Chapter 24 Optimal Stock Sizing in a Cutting Stock Problem with Stochastic Demands
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    Chapter 25 Stochastic Task Networks
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    Chapter 26 Rescheduling Railway Traffic on Real Time Situations Using Time-Interval Variables
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    Chapter 27 Dynamic Temporal Decoupling
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    Chapter 28 A Multi-stage Simulated Annealing Algorithm for the Torpedo Scheduling Problem
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    Chapter 29 Combining CP and ILP in a Tree Decomposition of Bounded Height for the Sum Colouring Problem
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    Chapter 30 htd – A Free, Open-Source Framework for (Customized) Tree Decompositions and Beyond
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    Chapter 31 The Nemhauser-Trotter Reduction and Lifted Message Passing for the Weighted CSP
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    Chapter 32 A Local Search Approach for Incomplete Soft Constraint Problems: Experimental Results on Meeting Scheduling Problems
Overall attention for this book and its chapters
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (72nd percentile)
  • High Attention Score compared to outputs of the same age and source (87th percentile)

Mentioned by

twitter
4 tweeters
wikipedia
1 Wikipedia page

Citations

dimensions_citation
1 Dimensions

Readers on

mendeley
50 Mendeley
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Title
Integration of AI and OR Techniques in Constraint Programming
Published by
arXiv, January 2017
DOI 10.1007/978-3-319-59776-8
ISBNs
978-3-31-959775-1, 978-3-31-959776-8
Authors

Emily Speakman, Han Yu, Jon Lee

Editors

Domenico Salvagnin, Michele Lombardi

Twitter Demographics

The data shown below were collected from the profiles of 4 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 50 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 50 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 6 12%
Researcher 5 10%
Student > Bachelor 4 8%
Student > Ph. D. Student 4 8%
Student > Doctoral Student 2 4%
Other 1 2%
Unknown 28 56%
Readers by discipline Count As %
Computer Science 9 18%
Engineering 6 12%
Biochemistry, Genetics and Molecular Biology 2 4%
Agricultural and Biological Sciences 1 2%
Chemistry 1 2%
Other 1 2%
Unknown 30 60%

Attention Score in Context

This research output has an Altmetric Attention Score of 5. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 08 September 2020.
All research outputs
#4,053,865
of 16,001,318 outputs
Outputs from arXiv
#83,821
of 637,628 outputs
Outputs of similar age
#71,861
of 267,782 outputs
Outputs of similar age from arXiv
#1,972
of 15,942 outputs
Altmetric has tracked 16,001,318 research outputs across all sources so far. This one has received more attention than most of these and is in the 74th percentile.
So far Altmetric has tracked 637,628 research outputs from this source. They receive a mean Attention Score of 3.9. This one has done well, scoring higher than 86% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 267,782 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 72% of its contemporaries.
We're also able to compare this research output to 15,942 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 87% of its contemporaries.