This book deals with an often-neglected feature of location problems, namely uncertainty, by combining two related fields: location theory and optimization. Written by leading researchers and practitioners in these fields, each chapter examines one aspect of the location process in different contexts, such as supply chains; location decisions under congestion; disaster management; design of resilient facilities; uncertainty in the health sector; and facility location in the retail sector under uncertainty. The book also addresses methodological aspects, such as chance-constrained approaches, heuristic algorithms, scenario approaches, and simulation. As such, it provides decision-makers with essential methods, tools and approaches to help them deal with these uncertainties. It is mainly intended for graduate students in the fields of operations research and logistics, as well as professionals in logistics and supply chain management.

This book provides a comprehensive introduction to nonlinear programming, featuring a broad range of applications and solution methods in the field of continuous optimization. It begins with a summary of classical results on unconstrained optimization, followed by a wealth of applications from a diverse mix of fields, e.g. location analysis, traffic planning, and water quality management, to name but a few. In turn, the book presents a formal description of optimality conditions, followed by an in-depth discussion of the main solution techniques. Each method is formally described, and then fully solved using a numerical example.

This book, companion to Foundations of Location Analysis (Springer, 2011), highlights some of the applications of location analysis within the spheres of businesses, those that deal with public services and applications that deal with law enforcement and first responders. While the Foundations book reviewed the theory and first contributions, this book describes how different location techniques have been used to solve real problems. Since many real problems comprise multiple objectives, in this book there is more presence of tools from multicriteria decision making and multiple-objective optimization. The section on business applications looks at such problems as locating bank branches, the potential location of a logistics park, sustainable forest management and layout problems in a hospital, a much more difficult type of problem than mere location problems. The section on public services presents chapters on the design of habitats for wildlife, control of forest fires, the location of intelligent sensors along highways for timely emergency response, locating breast cancer screening centers, an economic analysis for the locations of post offices and school location. The final section of the book includes chapters on the well-known problem of locating fire stations, a model for the location of sensors for travel time information, the problem of police districting, locations of jails, location of Coast Guard vessels and finally, a survey of military applications of location analysis throughout different periods of recent history.

Location analysis has matured from an area of theoretical inquiry that was designed to explain observed phenomena to a vibrant field which can be and has been used to locate items as diverse as landfills, fast food outlets, gas stations, as well as politicians and products in issue and feature spaces. Modern location science is dealt with by a diverse group of researchers and practitioners in geography, economics, operations research, industrial engineering, and computer science. Given the tremendous advances location science has seen from its humble beginnings, it is time to look back. The contributions in this volume were written by eminent experts in the field, each surveying the original contributions that created the field, and then providing an up-to-date review of the latest contributions. Specific areas that are covered in this volume include: * The three main fields of inquiry: minisum and minimax problems and covering models * Nonstandard location models, including those with competitive components, models that locate undesirable facilities, models with probabilistic features, and problems that allow interactions between facilities * Descriptions and detailed examinations of exact techniques including the famed Weiszfeld method, and heuristic methods ranging from Lagrangean techniques to Greedy algorithms * A look at the spheres of influence that the facilities generate and that attract customers to them, a topic crucial in planning retail facilities * The theory of central places, which, other than in mathematical games, where location science was born

The book presents a unified treatment of integer programming and network models with topics ranging from exact and heuristic algorithms to network flows, traveling salesman tours, and traffic assignment problems. While the emphasis of the book is on models and applications, the most important methods and algorithms are described in detail and illustrated by numerical examples. The formulations and the discussion of a large variety of models provides insight into their structures that allows the user to better evaluate the solutions to the problems.

In the pages of this text readers will find nothing less than a unified treatment of linear programming. Without sacrificing mathematical rigor, the main emphasis of the book is on models and applications. The most important classes of problems are surveyed and presented by means of mathematical formulations, followed by solution methods and a discussion of a variety of "what-if" scenarios. Non-simplex based solution methods and newer developments such as interior point methods are covered.

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.

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.

This book applies Multicriteria Decision Making (MCDM) tools and techniques to problems in location analysis. It begins with a generic model for MCDM and subsequently develops specific versions of the technique for particular location problems. Throughout the book, MCDM is understood to encompass all tools and techniques that choose or rank existing or feasible solutions, including discrete multi-attribute decision making (MADM) problems, which typically include an attribute table that specifies the consequences of each decision with regard to the given criteria, as well as multi-objective linear problems (MOLPs), which incorporate all objectives in a single optimization problem.  The book is organized as follows: the first four chapters introduce readers to the basic tools and techniques used in single-objective optimization, multicriteria decision making, location analysis, and other tools, such as statistical regression and geographical information systems. This is followed by ten chapters on model applications, each of which introduces readers to a specific location problem and applies one technique to solve it. The book is then wrapped up in a closing chapter that looks at the location process from a practitioner’s point of view.  This book is intended as a textbook for upper-undergraduate and master-level courses on location analysis. It will also benefit decision-makers who actually need to locate facilities. 

This book, companion to Foundations of Location Analysis (Springer, 2011), highlights some of the applications of location analysis within the spheres of businesses, those that deal with public services and applications that deal with law enforcement and first responders. While the Foundations book reviewed the theory and first contributions, this book describes how different location techniques have been used to solve real problems. Since many real problems comprise multiple objectives, in this book there is more presence of tools from multicriteria decision making and multiple-objective optimization. The section on business applications looks at such problems as locating bank branches, the potential location of a logistics park, sustainable forest management and layout problems in a hospital, a much more difficult type of problem than mere location problems. The section on public services presents chapters on the design of habitats for wildlife, control of forest fires, the location of intelligent sensors along highways for timely emergency response, locating breast cancer screening centers, an economic analysis for the locations of post offices and school location. The final section of the book includes chapters on the well-known problem of locating fire stations, a model for the location of sensors for travel time information, the problem of police districting, locations of jails, location of Coast Guard vessels and finally, a survey of military applications of location analysis throughout different periods of recent history.

Location analysis has matured from an area of theoretical inquiry that was designed to explain observed phenomena to a vibrant field which can be and has been used to locate items as diverse as landfills, fast food outlets, gas stations, as well as politicians and products in issue and feature spaces. Modern location science is dealt with by a diverse group of researchers and practitioners in geography, economics, operations research, industrial engineering, and computer science. Given the tremendous advances location science has seen from its humble beginnings, it is time to look back. The contributions in this volume were written by eminent experts in the field, each surveying the original contributions that created the field, and then providing an up-to-date review of the latest contributions. Specific areas that are covered in this volume include: * The three main fields of inquiry: minisum and minimax problems and covering models * Nonstandard location models, including those with competitive components, models that locate undesirable facilities, models with probabilistic features, and problems that allow interactions between facilities * Descriptions and detailed examinations of exact techniques including the famed Weiszfeld method, and heuristic methods ranging from Lagrangean techniques to Greedy algorithms * A look at the spheres of influence that the facilities generate and that attract customers to them, a topic crucial in planning retail facilities * The theory of central places, which, other than in mathematical games, where location science was born

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.

In the pages of this text readers will find nothing less than a unified treatment of linear programming. Without sacrificing mathematical rigor, the main emphasis of the book is on models and applications. The most important classes of problems are surveyed and presented by means of mathematical formulations, followed by solution methods and a discussion of a variety of "what-if" scenarios. Non-simplex based solution methods and newer developments such as interior point methods are covered.

This is the third edition of a textbook that has been used in a number of undergraduate courses and covers the standard models and techniques used in decision-making in organizations. The main emphasis of the book is on modelling business-related scenarios and the generation of decision alternatives. Fully solved examples from many areas are used to illustrate the main concepts without getting bogged down in technical details. The book presents an approach to operations research that is heavily based on modelling and makes extensive use of sensitivity analyses. It is the result of the authors' many years of combined teaching experience. The third edition includes new topics such as nonlinear programming and reliability theory, as well as additional material on multi-attribute decision-making. Each chapter includes a number of fully solved problems that allow students to practice or self-study. Additional problems are available on the book's accompanying website.

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.

This book provides a comprehensive introduction to nonlinear programming, featuring a broad range of applications and solution methods in the field of continuous optimization. It begins with a summary of classical results on unconstrained optimization, followed by a wealth of applications from a diverse mix of fields, e.g. location analysis, traffic planning, and water quality management, to name but a few. In turn, the book presents a formal description of optimality conditions, followed by an in-depth discussion of the main solution techniques. Each method is formally described, and then fully solved using a numerical example.

An Atlantic BestsellerNew Brunswick offers a dizzying array of hiking challenges, spectacular views, and amazing wildlife. In this expanded and updated fourth edition of Hiking Trails of New Brunswick, veteran trail enthusiasts Marianne and H.A. Eiselt lead hikers from one end of the province to the other, along river valleys, through provincial and national parks, along the coasts, and up and down mountains.Newly illustrated in full colour with striking photographs and maps, this comprehensive guide includes more than 100 trails, with detailed trail descriptions, tips, and sidebars on natural and historical features. Featuring up-to-the-minute information, the essential guide to hiking in New Brunswick has just become even better.

The purpose of this book is to provide readers with an introduction to the very active field of integer programming and network models. The idea is to cover the main parts of the field without being too detailed or too technical. As a matter of fact, we found it somewhat surprising that most--especially newer---books are strongly algorithmically oriented. In contrast, the main emphasis of this book is on models rather than methods. This focus expresses our view that methods are tools to solve actual problems and not ends in themselves. As such, graduate (and with some omissions, undergraduate) students may find this book helpful in their studies as will practitioners who would like to get acquainted with a field or use this text as a refresher. This premise has resulted in a coverage that omits material that is standard fare in other books, whereas it covers topics that are only infrequently found elsewhere. There are some, yet relatively few, prerequisites for the reader. Most material that is required for the understanding of more than one chapter is presented in one of the four chapters of the introductory part, which reviews the main results in linear programming, the analysis of algorithms, graphs and networks, and dynamic programming, respectively. Readers who are familiar with the issues involved can safely skip that part. The three main parts of the book rely on intuitive reasoning and examples, whenever practical, instead of theorems and proofs.

This is the third edition of a textbook that has been used in a number of undergraduate courses and covers the standard models and techniques used in decision-making in organizations. The main emphasis of the book is on modelling business-related scenarios and the generation of decision alternatives. Fully solved examples from many areas are used to illustrate the main concepts without getting bogged down in technical details. The book presents an approach to operations research that is heavily based on modelling and makes extensive use of sensitivity analyses. It is the result of the authors’ many years of combined teaching experience. The third edition includes new topics such as nonlinear programming and reliability theory, as well as additional material on multi-attribute decision-making. Each chapter includes a number of fully solved problems that allow students to practice or self-study. Additional problems are available on the book’s accompanying website.