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Evolutionary Computation in Combinatorial Optimization

Overview of attention for book
Evolutionary Computation in Combinatorial Optimization
Springer Berlin Heidelberg

Table of Contents

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    Book Overview
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    Chapter 1 A Methodology for Comparing the Execution Time of Metaheuristics Running on Different Hardware
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    Chapter 2 A Variable Neighborhood Search Approach for the Two-Echelon Location-Routing Problem
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    Chapter 3 An ILS-Based Metaheuristic for the Stacker Crane Problem
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    Chapter 4 An NSGA-II Algorithm for the Green Vehicle Routing Problem
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    Chapter 5 Clustering Search Heuristic for Solving a Continuous Berth Allocation Problem
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    Chapter 6 Combining Heuristic and Exact Methods to Solve the Vehicle Routing Problem with Pickups, Deliveries and Time Windows
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    Chapter 7 D 2 MOPSO : Multi-Objective Particle Swarm Optimizer Based on Decomposition and Dominance
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    Chapter 8 Domain Reduction Using GRASP Construction Phase for Transmission Expansion Planning Problem
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    Chapter 9 Electrical Load Management in Smart Homes Using Evolutionary Algorithms
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    Chapter 10 Exact Computation of the Fitness-Distance Correlation for Pseudoboolean Functions with One Global Optimum
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    Chapter 11 Genetic Algorithms for Scheduling Devices Operation in a Water Distribution System in Response to Contamination Events
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    Chapter 12 HyFlex: A Benchmark Framework for Cross-Domain Heuristic Search
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    Chapter 13 Hyper-Heuristic Based on Iterated Local Search Driven by Evolutionary Algorithm
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    Chapter 14 Intensification/Diversification-Driven ILS for a Graph Coloring Problem
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    Chapter 15 Iterated Greedy Algorithms for the Maximal Covering Location Problem
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    Chapter 16 Multiobjectivizing the HP Model for Protein Structure Prediction
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    Chapter 17 Multi-Pareto-Ranking Evolutionary Algorithm
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    Chapter 18 Pareto Local Search Algorithms for Anytime Bi-objective Optimization
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    Chapter 19 Pure Strategy or Mixed Strategy?
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    Chapter 20 Recurrent Genetic Algorithms: Sustaining Evolvability
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    Chapter 21 Splitting Method for Spatio-temporal Sensors Deployment in Underwater Systems
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    Chapter 22 The Vehicle Routing Problem with Backhauls: A Multi-objective Evolutionary Approach
Attention for Chapter 20: Recurrent Genetic Algorithms: Sustaining Evolvability
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Chapter title
Recurrent Genetic Algorithms: Sustaining Evolvability
Chapter number 20
Book title
Evolutionary Computation in Combinatorial Optimization
Published by
Springer, Berlin, Heidelberg, April 2012
DOI 10.1007/978-3-642-29124-1_20
Book ISBNs
978-3-64-229123-4, 978-3-64-229124-1
Authors

Adnan Fakeih, Ahmed Kattan

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 10 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Italy 1 10%
Malta 1 10%
Unknown 8 80%

Demographic breakdown

Readers by professional status Count As %
Student > Master 3 30%
Student > Ph. D. Student 2 20%
Researcher 2 20%
Student > Doctoral Student 1 10%
Professor > Associate Professor 1 10%
Other 0 0%
Unknown 1 10%
Readers by discipline Count As %
Computer Science 7 70%
Economics, Econometrics and Finance 1 10%
Social Sciences 1 10%
Unknown 1 10%