Hyper-Heuristics. Theory and Applications

Description

Foreword......Page 3 Preface......Page 5 Contents......Page 7 Acronyms & Notations......Page 11 --- Fundamentals & Theory......Page 12 1.2 Low-Level Heuristics......Page 13 1.3 Classification of Hyper-Heuristics......Page 14 2.1 Introduction......Page 16 2.2 Case-Based Reasoning......Page 17 2.3 Local Search Methods......Page 19 2.4 Population-Based Methods......Page 20 2.6 Discussion......Page 23 3.1 Introduction......Page 26 3.2.1 Heuristic Selection Techniques......Page 27 3.2.2 Move Acceptance Techniques......Page 29 3.3 Multipoint Search Selection Perturbative Hyper-Heuristics......Page 30 3.4 Discussion......Page 31 4.1 Introduction......Page 33 4.2 Attributes and Representation of Low-Level Heuristics......Page 34 4.3 Genetic Programming......Page 35 4.4 Disposability vs. Reusability......Page 36 4.5 Discussion......Page 37 5.1 Introduction......Page 40 5.3 Creating Algorithms and Meta-Heuristics......Page 41 5.4 Discussion......Page 42 6.1 Introduction......Page 44 6.2 A Formal Definition of Hyper-Heuristics......Page 45 6.2.1 Two Search Spaces Within the Formal Hyper-Heuristic Framework......Page 46 6.2.2 Fitness Landscape of the Heuristic Space in the Hyper-Heuristic Framework......Page 48 6.3.1 A Graph-Based Selection Hyper-Heuristic (GHH) Framework......Page 49 6.3.2 Analysis of Two Search Spaces in the GHH Framework......Page 50 6.3.3 Performance Evaluation of GHH......Page 51 6.3.4 Fitness Landscape Analysis on GHH......Page 52 6.4 Discussion......Page 54 --- Applications of Hyper-Heuristics......Page 56 7.1 Introduction......Page 57 7.2.1 Constructive Low-Level Heuristics in Vehicle Routing Problems......Page 58 7.3 Selection Hyper-Heuristics for Vehicle Routing Problems......Page 60 7.3.2 Selection Hyper-Heuristics with Both Constructive and Perturbative Low-Level Heuristics......Page 61 7.4 Generation Hyper-Heuristics for Vehicle Routing Problems......Page 62 7.5 Discussion......Page 65 8.1 Introduction......Page 67 8.2 Low-Level Heuristics for Nurse Rostering Problems......Page 68 8.3 Selection Hyper-Heuristics for Nurse Rostering Problems......Page 69 8.4 Discussion......Page 71 9.2 Selection Constructive Hyper-Heuristics......Page 73 9.2.1 Low-Level Constructive Heuristics for Bin Packing......Page 74 9.2.2 Methods Employed by the Hyper-Heuristics......Page 75 9.3 Generation Constructive Hyper-Heuristics......Page 76 9.4 Discussion......Page 79 10.2 Low-Level Constructive Heuristics for Examination Timetabling Problems......Page 80 10.3 Low-Level Perturbative Heuristics for Examination Timetabling Problems......Page 81 10.4.1 Selection Perturbative Hyper-Heuristics for Examination Timetabling Problems......Page 82 10.4.2 Selection Constructive Hyper-Heuristics for Examination Timetabling Problems......Page 83 10.5 Generation Hyper-Heuristics for Examination Timetabling Problems......Page 85 10.6 Discussion......Page 86 11.2 Cross-Domain Heuristic Search Challenge (CHeSC)......Page 88 11.3.1 Finalists of CHeSC 2011......Page 90 11.3.2 Recent Approaches......Page 92 11.4 Discussion......Page 93 --- Past, Present & Future......Page 94 12.2 Hybrid Hyper-Heuristics......Page 95 12.3 Hyper-Heuristics for Automated Design......Page 96 12.4 Automated Design of Hyper-Heuristics......Page 98 12.5 Continuous Optimization......Page 99 12.6 Discussion......Page 100 13 Conclusions & future Research Directions......Page 102 HyFlex & EvoHyp......Page 105 A.1 HyFlex......Page 106 A.2.2 GenProg......Page 108 A.2.4 Accessing EvoHyp......Page 109 Combinatorial Optimization Problems & Benchmarks......Page 110 B.1.2 Two-Dimensional Bin Packing......Page 111 B.1.4 Packing Benchmark Sets......Page 112 B.2 Nurse Rostering Problem......Page 113 B.2.3 The Nottingham Benchmark Nurse Rostering Dataset......Page 114 B.3 Vehicle Routing Problems......Page 115 B.4 Examination Timetabling Problems......Page 116 B.4.1 Exam Timetabling Benchmark Datasets......Page 117 Refs......Page 119 Index......Page 129