Buch, Englisch, 1641 Seiten, Format (B × H): 198 mm x 266 mm, Gewicht: 18899 g
ISBN: 978-1-4419-1137-7
Verlag: Springer US
The goal of the Encyclopedia of Operations Research and Management Science is to provide decision makers and problem solvers in business, industry, government, and academia a comprehensive overview of the wide range of ideas, methodologies, and synergistic forces that combine to form the preeminent decision-aiding fields of operations research and management science (OR/MS). The impact of OR/MS on the quality of life and economic well being of everyone is a story that deserves to be told in its full detail and glory. The Encyclopedia of Operations Research and Management Science is the prologue to that story.
The editors, working with the Encyclopedia’s Editorial Advisory Board, surveyed and divided OR/MS into specific topics that collectively encompass the foundations, applications, and emerging elements of this ever-changing field. We also wanted to establish the close associations that OR/MS has maintained with other scientific endeavors, with special emphasis on its symbiotic relationships with computer science, information systems, and mathematics. Based on our broad view of OR/MS, we enlisted a distinguished international group of academics and
practitioners to contribute articles on subjects for which they are renowned. We commissioned over 200 major expository articles and complemented them by numerous descriptions, discussions, definitions, and abbreviations. The connections between topics are highlighted by an entry’s final “See” statement, as appropriate. Each article provides a background or history of the topic, describes relevant applications, overviews present and future trends, and lists seminal and current references. To allow for variety in exposition, the authors were instructed to present their material from their research and applied perspectives. In particular, the authors, each of whom is a leading authority on the particular subject, were allowed to use whatever mathematical notation they felt was standard fortheir topics.
The Encyclopedia’s intended audience is technically diverse and wide; it includes anyone concerned with the science, techniques, and ideas of how one makes decisions. As this audience encompasses many professions, educational background and skills, we were attentive to the form, format, and scope of the articles. Thus, the articles are designed to serve as initial sources of information for all such readers, with special emphasis on the needs of students.
Zielgruppe
Professional/practitioner
Autoren/Hrsg.
Fachgebiete
Weitere Infos & Material
Many of the 2nd edition articles have been updated by the original authors, with a few being totally rewritten by new authors. In addition, the following completely new articles have been added, each of which either describes a new topic or replaces a previous short entry:
- Agent-Based Simulation
- Air Traffic Management
- Approximate Dynamic Programming
- Business Intelligence
- Closed-loop Supply Chains
- Combinatorial Auction Theory
- Community OR
- Complementarity Applications
- Computational Biology
- Conditional Value at Risk
- Convex Optimization
- Critical Systems Thinking
- Data Warehousing
- Decision Analysis Practice
- Deep Uncertainty
- Differential Games
- Disaster Management
- Disease Prevention, Detection, and Treatment
- Financial Engineering
- Flexible Manufacturing Systems
- Fuzzy Sets, Systems, and Applications
- Global Optimization
- Health Care Management
- Health Care Strategic Decision Making
- Heuristics
- Hit and Run Methods
- Influence Diagrams
- Knowledge Management
- Lagrangian Relaxation
- Markov Chain Monte Carlo
- Metaheuristics
- Music
- Open Source Software (and COIN-OR)
- Operational Research Society
- Petroleum Refining
- Quadratic Assignment Problem
- Rare Event Simulation
- Regenerative Simulation
- Response Surface Methodology
- Revenue Management
- Sample Average Approximation
- Sensitivity Analysis
- Service Science
- Simulated Annealing
- Societal Complexity
- Statistical Ranking and Selection
- Stochastic Approximation
- Stochastic Input Model Selection