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Evolutionary Computation in Combinatorial Optimization

Overview of attention for book
Cover of 'Evolutionary Computation in Combinatorial Optimization'

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 1 A Computational Study of Neighborhood Operators for Job-Shop Scheduling Problems with Regular Objectives
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    Chapter 2 A Genetic Algorithm for Multi-component Optimization Problems: The Case of the Travelling Thief Problem
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    Chapter 3 A Hybrid Feature Selection Algorithm Based on Large Neighborhood Search
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    Chapter 4 A Memetic Algorithm to Maximise the Employee Substitutability in Personnel Shift Scheduling
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    Chapter 5 Construct, Merge, Solve and Adapt Versus Large Neighborhood Search for Solving the Multi-dimensional Knapsack Problem: Which One Works Better When?
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    Chapter 6 Decomposing SAT Instances with Pseudo Backbones
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    Chapter 7 Efficient Consideration of Soft Time Windows in a Large Neighborhood Search for the Districting and Routing Problem for Security Control
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    Chapter 8 Estimation of Distribution Algorithms for the Firefighter Problem
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    Chapter 9 LCS-Based Selective Route Exchange Crossover for the Pickup and Delivery Problem with Time Windows
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    Chapter 10 Multi-rendezvous Spacecraft Trajectory Optimization with Beam P-ACO
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    Chapter 11 Optimizing Charging Station Locations for Electric Car-Sharing Systems
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    Chapter 12 Selection of Auxiliary Objectives Using Landscape Features and Offline Learned Classifier
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    Chapter 13 Sparse, Continuous Policy Representations for Uniform Online Bin Packing via Regression of Interpolants
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    Chapter 14 The Weighted Independent Domination Problem: ILP Model and Algorithmic Approaches
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    Chapter 15 Towards Landscape-Aware Automatic Algorithm Configuration: Preliminary Experiments on Neutral and Rugged Landscapes
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    Chapter 16 Understanding Phase Transitions with Local Optima Networks: Number Partitioning as a Case Study
Attention for Chapter 16: Understanding Phase Transitions with Local Optima Networks: Number Partitioning as a Case Study
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (73rd percentile)
  • High Attention Score compared to outputs of the same age and source (92nd percentile)

Mentioned by

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8 X users

Citations

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Readers on

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18 Mendeley
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Chapter title
Understanding Phase Transitions with Local Optima Networks: Number Partitioning as a Case Study
Chapter number 16
Book title
Evolutionary Computation in Combinatorial Optimization
Published in
Lecture notes in computer science, March 2017
DOI 10.1007/978-3-319-55453-2_16
Book ISBNs
978-3-31-955452-5, 978-3-31-955453-2
Authors

Gabriela Ochoa, Nadarajen Veerapen, Fabio Daolio, Marco Tomassini, Ochoa, Gabriela, Veerapen, Nadarajen, Daolio, Fabio, Tomassini, Marco

X Demographics

X Demographics

The data shown below were collected from the profiles of 8 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 18 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 18 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 28%
Lecturer 2 11%
Student > Master 2 11%
Researcher 2 11%
Student > Postgraduate 2 11%
Other 0 0%
Unknown 5 28%
Readers by discipline Count As %
Computer Science 10 56%
Business, Management and Accounting 1 6%
Agricultural and Biological Sciences 1 6%
Medicine and Dentistry 1 6%
Unknown 5 28%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 27 February 2019.
All research outputs
#4,551,997
of 22,963,381 outputs
Outputs from Lecture notes in computer science
#1,478
of 8,137 outputs
Outputs of similar age
#81,999
of 307,884 outputs
Outputs of similar age from Lecture notes in computer science
#9
of 113 outputs
Altmetric has tracked 22,963,381 research outputs across all sources so far. Compared to these this one has done well and is in the 80th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,137 research outputs from this source. They receive a mean Attention Score of 5.0. This one has done well, scoring higher than 81% 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 307,884 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 73% of its contemporaries.
We're also able to compare this research output to 113 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 92% of its contemporaries.