This book collects innovative research presented at the 17th Conference of the Association of Geographic Information Laboratories for Europe (AGILE) on Geographic Information Science, held in 2014 in Castellon, Spain. The scientific papers cover a variety of fundamental research topics as well as applied research in Geospatial Information Science, including measuring spatiotemporal phenomena, crowdsourcing and VGI, geosensor networks, indoor navigation, spatiotemporal analysis, modeling and visualization, spatiotemporal decision support, digital earth and spatial information infrastructures. The book is intended for researchers, practitioners, and students working in various fields and disciplines related to Geospatial Information Science and technology.
The purpose of this book is to provide readers with an introduction to the fields of decision making, location analysis, and project and machine scheduling. The combination of these topics is not an accident: decision analysis can be used to investigate decision seenarios in general, location analysis is one of the prime examples of decision making on the strategic Ievel, project scheduling is typically concemed with decision making on the tactical Ievel, and machine scheduling deals with decision making on the operational Ievel. Some of the chapters were originally contributed by different authors, and we have made every attempt to unify the notation, style, and, most importantly, the Ievel of the exposition. Similar to our book on Integer Programming and Network Models (Eiselt and Sandblom, 2000), the emphasis of this volume is on models rather than solution methods. This is particularly important in a book that purports to promote the science of decision making. As such, advanced undergraduate and graduate students, as weil as practitioners, will find this volume beneficial. While different authors prefer different degrees of mathematical sophistication, we have made every possible attempt to unify the approaches, provide clear explanations, and make this volume accessible to as many readers as possible.
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