Nelishia Pillay is a professor in the Department of Computer Science at the University of Pretoria in Gauteng, South Africa. One of her main areas of research is hyper-heuristics. She has co-authored the book Hyper-Heuristics: Theory and Applications (Springer, 2018) together with Rong Qu. She has previously served as the chair of the IEEE Task Force on Hyper-Heuristics. She has presented 18 tutorials on hyper-heuristics at capstone international conferences in the field. She has authored/co-authored more than 40 peer reviewed research papers on hyper-heuristics.Rong Qu is a professor in the School of Computer Science at the University of Nottingham, UK. Her main research interests include the modelling and optimization algorithms in scheduling and evolutionary algorithms for optimisation problems. In addition to the previous joint-authored book with Nelishia Pillay on hyper-heuristics, she has published more than 90 papers on intelligent optimisation algorithms at high impact journals since 2000.

• Chapter 1: Introduction.- Chapter 2: Generalization Levels of Hyper-Heuristics.- Chapter 3: Evaluation of Hyper-Heuristic Performance.- Chapter 4 - Standardization of Hyper-Heuristics.- Chapter 5: Automated Design Using Hyper-Heuristics.- Chapter 6: Machine Learning in Hyper-Heuristics.- Chapter 7: Cross-Domain Hyper-Heuristics Revisited.- Chapter 8: Hybrid Hyper-Heuristics.- Chapter 9: Hyper-Heuristics for Continuous Optimization.- Chapter 10: Explainable Hyper-Heuristics.- Chapter 11: Automated Design of Hyper-Heuristics.- Chapter 12: Transfer Learning in Hyper-Heuristics.- Chapter 13: Future Research Directions.- Chapter 14: Conclusions.

Nelishia Pillay is a professor in the Department of Computer Science at the University of Pretoria in Gauteng, South Africa. One of her main areas of research is hyper-heuristics. She has co-authored the book Hyper-Heuristics: Theory and Applications (Springer, 2018) together with Rong Qu. She has previously served as the chair of the IEEE Task Force on Hyper-Heuristics. She has presented 18 tutorials on hyper-heuristics at capstone international conferences in the field. She has authored/co-authored more than 40 peer reviewed research papers on hyper-heuristics.Rong Qu is a professor in the School of Computer Science at the University of Nottingham, UK. Her main research interests include the modelling and optimization algorithms in scheduling and evolutionary algorithms for optimisation problems. In addition to the previous joint-authored book with Nelishia Pillay on hyper-heuristics, she has published more than 90 papers on intelligent optimisation algorithms at high impact journals since 2000.

• Chapter 1: Introduction.- Chapter 2: Generalization Levels of Hyper-Heuristics.- Chapter 3: Evaluation of Hyper-Heuristic Performance.- Chapter 4 - Standardization of Hyper-Heuristics.- Chapter 5: Automated Design Using Hyper-Heuristics.- Chapter 6: Machine Learning in Hyper-Heuristics.- Chapter 7: Cross-Domain Hyper-Heuristics Revisited.- Chapter 8: Hybrid Hyper-Heuristics.- Chapter 9: Hyper-Heuristics for Continuous Optimization.- Chapter 10: Explainable Hyper-Heuristics.- Chapter 11: Automated Design of Hyper-Heuristics.- Chapter 12: Transfer Learning in Hyper-Heuristics.- Chapter 13: Future Research Directions.- Chapter 14: Conclusions.

Nelishia Pillay is a professor in the Department of Computer Science at the University of Pretoria in Gauteng, South Africa. One of her main areas of research is hyper-heuristics. She has co-authored the book Hyper-Heuristics: Theory and Applications (Springer, 2018) together with Rong Qu. She has previously served as the chair of the IEEE Task Force on Hyper-Heuristics. She has presented 18 tutorials on hyper-heuristics at capstone international conferences in the field. She has authored/co-authored more than 40 peer reviewed research papers on hyper-heuristics.Rong Qu is a professor in the School of Computer Science at the University of Nottingham, UK. Her main research interests include the modelling and optimization algorithms in scheduling and evolutionary algorithms for optimisation problems. In addition to the previous joint-authored book with Nelishia Pillay on hyper-heuristics, she has published more than 90 papers on intelligent optimisation algorithms at high impact journals since 2000.

• Chapter 1: Introduction.- Chapter 2: Generalization Levels of Hyper-Heuristics.- Chapter 3: Evaluation of Hyper-Heuristic Performance.- Chapter 4 - Standardization of Hyper-Heuristics.- Chapter 5: Automated Design Using Hyper-Heuristics.- Chapter 6: Machine Learning in Hyper-Heuristics.- Chapter 7: Cross-Domain Hyper-Heuristics Revisited.- Chapter 8: Hybrid Hyper-Heuristics.- Chapter 9: Hyper-Heuristics for Continuous Optimization.- Chapter 10: Explainable Hyper-Heuristics.- Chapter 11: Automated Design of Hyper-Heuristics.- Chapter 12: Transfer Learning in Hyper-Heuristics.- Chapter 13: Future Research Directions.- Chapter 14: Conclusions.