Clearly written and cutting edge, this book will appeal not only to GIS practitioners and researchers, but also to other professionals confronted by spatial problems. It may also serve as a primary textbook for college-level courses in GIS, advanced spatial modeling method and information engineering, or as a supplementary textbook for computer science courses.Clearly written and cutting edge, this book will appeal not only to GIS practitioners and researchers, but also to other professionals confronted by spatial problems. It may also serve as a primary textbook for college-level courses in GIS, advanced spatial modeling method and information engineering, or as a supplementary textbook for computer science courses.

• Michael F. Goodchild: Foreword Contributors Part I. Evolutionary Algorithms: An Introduction 1: Concepts of Evolutionary Modeling and Evolutionary Algorithms Part II. Spatial Evolutionary Modeling: Algorithms and Models 2: Modeling Spatial Phenomena Part III. Spatial Evolutionary Algorithms: Applications 3: Catherine Dibble: Beyond Data: Handling Spatial and Analytical Contexts with Genetics-Based Machine Learning 4: Christopher Brooks: A Genetic Algorithm to Design Optimal Patch Configurations Using Raster Data Structures 5: Steven Van Dijk, Dirk Thierens, and Mark De Berg: Designing Genetic Algorithms to Solve GIS Problems 6: Ângela Guimarães Pereira: Evolutionary Modeling of Routes: The Case of Road Design 7: Daniel Delahaye: Airspace Sectoring by Evolutionary Computation Index