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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
Overall attention for this book and its chapters
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Evolutionary Computation in Combinatorial Optimization
Published by
Springer Berlin Heidelberg, March 2012
DOI 10.1007/978-3-642-29124-1
978-3-64-229123-4, 978-3-64-229124-1

Hao, Jin-Kao, Middendorf, Martin

Twitter Demographics

The data shown below were collected from the profiles of 2 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 8 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 8 100%

Demographic breakdown

Readers by professional status Count As %
Other 1 13%
Student > Doctoral Student 1 13%
Unknown 6 75%
Readers by discipline Count As %
Business, Management and Accounting 1 13%
Computer Science 1 13%
Unknown 6 75%