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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 A Hybrid Constructive Mat-heuristic Algorithm for the Heterogeneous Vehicle Routing Problem with Simultaneous Pick-up and Delivery
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    Chapter 2 A Property Preserving Method for Extending a Single-Objective Problem Instance to Multiple Objectives with Specific Correlations
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    Chapter 3 An Evolutionary Approach to the Full Optimization of the Traveling Thief Problem
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    Chapter 4 Construct, Merge, Solve and Adapt: Application to the Repetition-Free Longest Common Subsequence Problem
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    Chapter 5 Deconstructing the Big Valley Search Space Hypothesis
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    Chapter 6 Determining the Difficulty of Landscapes by PageRank Centrality in Local Optima Networks
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    Chapter 7 Efficient Hill Climber for Multi-Objective Pseudo-Boolean Optimization
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    Chapter 8 Evaluating Hyperheuristics and Local Search Operators for Periodic Routing Problems
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    Chapter 9 Evolutionary Algorithms for Finding Short Addition Chains: Going the Distance
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    Chapter 10 Experimental Evaluation of Two Approaches to Optimal Recombination for Permutation Problems
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    Chapter 11 Hyperplane Elimination for Quickly Enumerating Local Optima
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    Chapter 12 Limits to Learning in Reinforcement Learning Hyper-heuristics
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    Chapter 13 Modifying Colourings Between Time-Steps to Tackle Changes in Dynamic Random Graphs
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    Chapter 14 Particle Swarm Optimisation with Sequence-Like Indirect Representation for Web Service Composition
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    Chapter 15 Particle Swarm Optimization for Multi-Objective Web Service Location Allocation
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    Chapter 16 Sim-EDA: A Multipopulation Estimation of Distribution Algorithm Based on Problem Similarity
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    Chapter 17 Solving the Quadratic Assignment Problem with Cooperative Parallel Extremal Optimization
Overall attention for this book and its chapters
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (73rd percentile)
  • Above-average Attention Score compared to outputs of the same age and source (59th percentile)

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