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Evolutionary Computation in Combinatorial Optimization

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Cover of 'Evolutionary Computation in Combinatorial Optimization'

Table of Contents

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    Book Overview
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    Chapter 1 On Monte Carlo Tree Search for Weighted Vertex Coloring
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    Chapter 2 A RNN-Based Hyper-heuristic for Combinatorial Problems
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    Chapter 3 Algorithm Selection for the Team Orienteering Problem
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    Chapter 4 Performance Evaluation of a Parallel Ant Colony Optimization for the Real-Time Train Routing Selection Problem in Large Instances
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    Chapter 5 Deep Infeasibility Exploration Method for Vehicle Routing Problems
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    Chapter 6 Evolutionary Algorithms for the Constrained Two-Level Role Mining Problem
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    Chapter 7 Simplifying Dispatching Rules in Genetic Programming for Dynamic Job Shop Scheduling
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    Chapter 8 Novelty-Driven Binary Particle Swarm Optimisation for Truss Optimisation Problems
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    Chapter 9 A Beam Search for the Shortest Common Supersequence Problem Guided by an Approximate Expected Length Calculation
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    Chapter 10 Modeling the Costas Array Problem in QUBO for Quantum Annealing
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    Chapter 11 Penalty Weights in QUBO Formulations: Permutation Problems
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    Chapter 12 PUBO $$_i$$ i : A Tunable Benchmark with Variable Importance
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    Chapter 13 Stagnation Detection Meets Fast Mutation
Attention for Chapter 9: A Beam Search for the Shortest Common Supersequence Problem Guided by an Approximate Expected Length Calculation
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Chapter title
A Beam Search for the Shortest Common Supersequence Problem Guided by an Approximate Expected Length Calculation
Chapter number 9
Book title
Evolutionary Computation in Combinatorial Optimization
Published by
Springer, Cham, January 2022
DOI 10.1007/978-3-031-04148-8_9
Book ISBNs
978-3-03-104147-1, 978-3-03-104148-8
Authors

Mayerhofer, Jonas, Kirchweger, Markus, Huber, Marc, Raidl, Günther

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