Natural computing is one of the most exciting developments in computer science, and there is a growing consensus that it will become a major field in computer science in this country.
Prof Nelishia Pillay, Head of the Department of Computer Science in the Faculty of Engineering, Built Environment and Information Technology at the University of Pretoria, has published a book, titled Hyper-heuristics: Theory and applications in the Springer Natural Computing Series. In this book, Prof Pillay and co-author, Prof Rong Qu, aim to solve real-world optimisation problems and present fundamental theory and applications of hyper-heuristics.
This introduction to the field of hyper-heuristics presents the required foundations and tools, illustrating some of their applications and highlighting advances in the field and future research directions. The book comprises 13 chapters, organised into three parts. The first part of the book focuses on hyper-heuristic fundamentals and theory and gives an overview of selection-constructive, selection-perturbative, generation-constructive and generation-perturbative hyper-heuristics, and a formal definition of hyper-heuristics. The second part presents various applications of hyper-heuristics such as vehicle routing, nurse rostering, packing and examination timetabling. Advanced topics, a summary of the field and future research directions, are described in the third part of the book. The HyFlex framework and the EvoHyp toolkit, together with additional information on the combinatorial optimisation problems presented in the second part of the book, are included in the appendices.
This is the first book on hyper-heuristics since the inception of the field and serves as a reference for researchers wanting an introduction to hyper-heuristics as well as those that want to extend their knowledge of the domain. Reviews of the book describe it as ‘the first place to look, when starting a new project in the area’ and ‘a single reference for anybody that has an interest in hyper-heuristics’.
In addition to her position as head of the Department of Computer Science, Prof Pillay is also co-chair of the new MultiChoice Chair of Machine Learning and her research interests include hyper-heuristics, combinatorial optimisation, genetic programming, genetic algorithms and other nature-inspired methods.