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Evolutionary Computation in Combinatorial Optimization

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

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 A Critical Element-Guided Perturbation Strategy for Iterated Local Search
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    Chapter 2 A Genetic Algorithm for Net Present Value Maximization for Resource Constrained Projects
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    Chapter 3 A Hybrid Algorithm for Computing Tours in a Spare Parts Warehouse
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    Chapter 4 A New Binary Description of the Blocks Relocation Problem and Benefits in a Look Ahead Heuristic
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    Chapter 5 A Plasmid Based Transgenetic Algorithm for the Biobjective Minimum Spanning Tree Problem
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    Chapter 6 A Tabu Search Algorithm with Direct Representation for Strip Packing
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    Chapter 7 An ACO Approach to Planning
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    Chapter 8 An Artificial Immune System for the Multi-Mode Resource-Constrained Project Scheduling Problem
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    Chapter 9 Beam-ACO Based on Stochastic Sampling for Makespan Optimization Concerning the TSP with Time Windows
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    Chapter 10 Binary Exponential Back Off for Tabu Tenure in Hyperheuristics
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    Chapter 11 Diversity Control and Multi-Parent Recombination for Evolutionary Graph Coloring Algorithms
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    Chapter 12 Divide-And-Evolve Facing State-of-the-Art Temporal Planners during the 6 th International Planning Competition
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    Chapter 13 Exact Solutions to the Traveling Salesperson Problem by a Population-Based Evolutionary Algorithm
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    Chapter 14 Finding Balanced Incomplete Block Designs with Metaheuristics
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    Chapter 15 Guided Ejection Search for the Job Shop Scheduling Problem
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    Chapter 16 Improving Performance in Combinatorial Optimisation Using Averaging and Clustering
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    Chapter 17 Iterated Local Search for Minimum Power Symmetric Connectivity in Wireless Networks
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    Chapter 18 Metropolis and Symmetric Functions: A Swan Song
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    Chapter 19 Robustness Analysis in Evolutionary Multi-Objective Optimization Applied to VAR Planning in Electrical Distribution Networks
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    Chapter 20 Staff Scheduling with Particle Swarm Optimisation and Evolution Strategies
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    Chapter 21 University Course Timetabling with Genetic Algorithm: A Laboratory Excercises Case Study
Overall attention for this book and its chapters
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Mentioned by

wikipedia
1 Wikipedia page

Readers on

mendeley
2 Mendeley
Summary Wikipedia
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Evolutionary Computation in Combinatorial Optimization
Published by
ADS, April 2009
DOI 10.1007/978-3-642-01009-5
ISBNs
978-3-64-201008-8, 978-3-64-201009-5
Editors

Cotta, Carlos, Cowling, Peter, Cotta, Carlos, Cowling, Peter

View on publisher site
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 2 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 2 100%

Demographic breakdown

Readers by professional status Count As %
Professor 1 50%
Student > Ph. D. Student 1 50%
Readers by discipline Count As %
Computer Science 1 50%
Engineering 1 50%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 10 July 2019.
All research outputs
#7,552,525
of 23,039,416 outputs
Outputs from ADS
#9,313
of 37,451 outputs
Outputs of similar age
#33,198
of 93,996 outputs
Outputs of similar age from ADS
#98
of 369 outputs
Altmetric has tracked 23,039,416 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 37,451 research outputs from this source. They receive a mean Attention Score of 4.6. This one is in the 29th percentile – i.e., 29% of its peers scored the same or lower than it.
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 93,996 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 19th percentile – i.e., 19% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 369 others from the same source and published within six weeks on either side of this one. This one is in the 13th percentile – i.e., 13% of its contemporaries scored the same or lower than it.

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