Review
This is the kind of book that all students interested in search and optimization should read. Almost half of the book is devoted to laying a foundation for understanding search and optimization for both heuristic methods and more traditional exact methods. This is really why the book is so valuable. It puts heuristic search in context, and this integrated view is important and is often lacking in other books on modern heuristic search. The book then goes on to provide an excellent tutorial level discussion of heuristic methods such as evolutionary algorithms, variable neighborhood search, iterated local search and tabu search. The book is a valuable contribution to the field. Other books have tried to provide the same breadth by collecting together tutorials by multiple authors. But Prof. Rothlauf's book is stronger because it provides an integrated and unified explanation of modern heuristic methods. Darrell Whitley (Colorado State University, Chair of SIGEVO, former Editor-in-Chief of the journal Evolutionary Computation) The book by Franz Rothlauf is interesting in many ways. First, it goes much further than a simple description of the most important modern heuristics; it provides insight into the reasons that explain the success of some methods. Another attractive feature of the book is its thorough, yet concise, treatment of the complete scope of optimization methods, including techniques for continuous optimization; this allows optimization methods, including techniques for continuous optimization; this allows readers with a limited background in optimization to gain a deeper appreciation of the modern heuristics that are the main topic of the book. Finally, the case studies presented provide a nice illustration of the application of modern heuristics to challenging and highly relevant problems. Michel Gendreau (École Polytechnique de Montréal, former Vice-President of the International Federation of Operational Research Societies (IFORS) and the Institute for Operations Research and Management Science (INFORMS), Editor-in-Chief of the journal Transportation Science) Franz Rothlauf’s new book, "Design of Modern Heuristics: Principles and Application", is a celebration of computer science at its best, combining a blend of mathematical analysis, empirical inquiry, conceptual modeling, and useful application to give readers a principled and practical overview of heuristics in modern problem solving. Despite years of successful experience to the contrary, some still use the word “heuristic” as a putdown or dirty word, suggesting that any computational procedure not formally proven to converge on some particular class of problem is somehow not worthy of study or even polite discussion. Rothlauf’s intelligent text sets such folly aside, helping readers to understand that a principled approach can be taken to those computational objects that defy simple mathematical description or elucidation, helping readers to separate the wheat from the computational chaff clearly and systematically to practical end. David E. Goldberg (University of Illinois at Urbana-Champaign, author of “Genetic Algorithms in Search, Optimization, and Machine Learning” and “The Design of Innovation”) The book on modern heuristic methods by Franz Rothlauf is very special as it has very strong practical flavour – it teaches us how to design efficient and effective modern heuristics to solve a particular problem. This empasis on design component resulted in in-depth discussion on topics like: for which types of problems we should use modern heuristics, how we can select a modern heuristic that is well-suited to our problem, what are basic principles for the design of modern heuristics, and how we can use problem-specific knowledge for the design of modern heuristics? I recommend this book highly to the whole optimization research community and, in particular, to every practitioner who is interested in the applicability of modern heuristic methods. Zbigniew Michalewicz (University of Adelaide, author of “How to Solve It: Modern Heuristics”)
From the Back Cover
Most textbooks on modern heuristics provide the reader with detailed descriptions of the functionality of single examples like genetic algorithms, genetic programming, tabu search, simulated annealing, and others, but fail to teach the underlying concepts behind these different approaches.
The author takes a different approach in this textbook by focusing on the users' needs and answering three fundamental questions: First, he tells us which problems modern heuristics are expected to perform well on, and which should be left to traditional optimization methods. Second, he teaches us to systematically design the "right" modern heuristic for a particular problem by providing a coherent view on design elements and working principles. Third, he shows how we can make use of problem-specific knowledge for the design of efficient and effective modern heuristics that solve not only small toy problems but also perform well on large real-world problems.
This book is written in an easy-to-read style and it is aimed at students and practitioners in computer science, operations research and information systems who want to understand modern heuristics and are interested in a guide to their systematic design and use.
