Autorentext
H. A. Eiselt is a Professor in the Faculty of Business Administration at the University of New Brunswick, Canada. He joined the Faculty of Business Administration in 1986 and is a member of the Quantitative Methods Area. He teaches Quantitative Analysis and Location Theory in the BBA program. Dr. Eiselt received the UNB Merit Award in 1991 and 2016. He received the Faculty of Business Administration's Excellence in Research Award in 1998, 2003, and 2015 for outstanding performance across his career. He is Associate Editor of INFOR. He is also a member of the Advisory or Editorial Boards of Computers & Operations Research, and the International Journal of Operations, Quantitative Management. He has published 115 articles in scientific journals as well as ten books with Springer. His main interests are in the fields of location theory, decision analysis, and optimization.
**Vladimir Marianov** is a Professor in the Electrical Engineering Department at the Pontificia Universidad Católica de Chile in Santiago, Chile. His research and teaching interests are in the areas of facility location and network design, as well as telecommunications. He has published over 75 papers on location of public services (schools, prisons, and landfills), location under congestion (bank branches, primary health services) and location of competitive facilities, including multipurpose shopping. He has co-edited several books, as well as authored several book chapters, on subjects including Location of Emergency Systems, Location in the Public Sector, Location of Jails, and Competitive Location. He is a member of the editorial or advisory boards of Computers & Operations Research, OR Spectrum and TOP. He received the biennial College of Engineering Award for Excellence in 2016.

Klappentext
This book is a volume in honor of Zvi Drezner's 75th birthday. Professor Drezner is a leading scholar in location science. He received his BSc degree in Mathematics in 1965 and his PhD. in Computer Science ten years later, both from the Technion in Haifa, Israel. Since 1978 he has published in excess of 300 papers in refereed journals and books. He has received many honors, among them the University Outstanding Professor in 2005-6, the Outstanding Research Award (both from Cal State-Fullerton), the Location Analysis Lifetime Achievement Award from the Society for Location Analysis, and was named a Lifetime Fellow in INFORMS.Zvi has worked in a variety of fields, but most prominently in continuous location models. His main contributions include a 1982 paper on competitive location analysis, which was the first contribution to formally use the von Stackelberg leader-follower concept in the plane, contributions in 1989 (along with many others) on the Weber problem, and work with Oded Berman on the p-median under uncertainty in 2008. He has also enriched the literature by many contributions that devise genetic algorithms and tabu search techniques (both heuristic algorithms), as well as global optimization techniques, such as the big-triangle-small-triangle method, applied to location problems.The chapters of the book have been chosen to provide readers with a large variety of topics in the field of location science, which normally are available only in many different specialist journals. In addition to easily approachable surveys, the contributions, written by the top specialists in the field, present the latest results as well.

Inhalt
Chapter 1. My Career and Contributions.- Chapter 2. Understanding the Weber Location Paradigm.- Chapter 3. A general framework for local search applied to the continuous p-median problem.- Chapter 4. Big Triangle Small Triangle Method for the Weber Problem on the Sphere.- Chapter 5. Integer Location Problems.- Chapter 6. Continuous Location Problems.- Chapter 7. Voting for locating facilities: The wisdom of voters.- Chapter 8. Innovations in Statistical Analysis and Genetic Algorithms.- Chapter 9. Hub Location and Related Models.- Chapter 10. Gravity Models in Competitive Facility Location.- Chapter 11. Cover-Based Competitive Location Models.- Chapter 12. The Mean-Value-at-Risk Median Problem on a Network with Random Demand Weights.- Chapter 13. A Bivariate Exponential Distribution.