Operations Research and Management

Quantitative Methods for Planning and Decision-Making in Business and Economics
Erscheinungsjahr 2025
ISBN: 978-3-031-47208-4
Verlag: Springer Nature Switzerland

Buch, Englisch, 270 Seiten, Format (B × H): 148 mm x 210 mm, Gewicht: 376 g

Reihe: Springer Texts in Business and Economics

This textbook introduces quantitative methods in operations management, based on operational research. Written for undergraduate and graduate students as well as practitioners, this book serves as a valuable compendium of essential tools for project planning, control, and strategic decision-making.

Drawing from the expertise of both experienced scientists and seasoned practical managers, the descriptions of each tool are a harmonious blend of theoretical insights and real-world applicability. With a focus on accessibility, the authors have thoughtfully combined abstract concepts with easy-to-follow examples and detailed case studies.

Readers will benefit from the abundance of well-explained recommendations and practical problem-solving approaches, where the book offers guidance on how to solve presented issues by using commercial software. Whether one seeks to refine project management, optimize operations, or make strategic choices, this book equips readers with theknowledge and proficiency required to excel in the dynamic field of operations management.

Zielgruppe

Upper undergraduate

Autoren/Hrsg.

Neifer, Thomas

Peren, Franz W.

Fachgebiete

• Wirtschaftswissenschaften Betriebswirtschaft Unternehmensforschung
• Wirtschaftswissenschaften Betriebswirtschaft Bereichsspezifisches Management Produktionsmanagement, Qualitätskontrolle
• Mathematik | Informatik Mathematik Operations Research
• Wirtschaftswissenschaften Betriebswirtschaft Management Projektmanagement
• Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Angewandte Mathematik, Mathematische Modelle
• Wirtschaftswissenschaften Betriebswirtschaft Wirtschaftsmathematik und -statistik

Inhaltsverzeichnis

Linear Optimization and Heuristics:  K. Völker, M. Hümmer:The Decision Tree Procedure.- F. W. Peren: Linear Optimization.- K. M. Kroth: Cutting and Packaging Optimization.- M. Adolphs, S. Feistner, V. Jahnke: Queueing Theory.- T. Neifer, F. W. Peren: Sequencing Problems.- T. Neifer: Regression Analysis Using Dummy Variables.- L. Schwarzbach, R. Schmitt: Heuristic Methods.- Simulation: A. Wachholz, R. Malzew: Simulation Processes in Business and Economics: Fundamentals of the Monte Carlo Simulation.- T. Neifer: Markov Chain Monte Carlo Methods.- Nonlinear Optimization: F. W. Peren: Nonlinear Optimization: The Nelder-Mead Simlex Search Procedure.- T. Neifer, D. Lawo: Dynamic Programming.- Project Management: M. Krebs: Network Analysis Method.- R. Clement, F. W. Peren: Peren-Clement Index (PCI).- The Peren Theorem. 

Über Autor(innen)

Franz W. Peren is a professor of business administration at the Bonn-Rhein-Sieg University, Germany, specializing in quantitative methods. He has been teaching business mathematics, business statistics, and quantitative methods in planning, taxation, and controlling within operational and strategic management since 1993, mainly at German universities of applied sciences. He has also taught and conducted research as a visiting professor at the University of Victoria in Victoria, BC, Canada, and at Columbia University in New York City, USA. Peren's practical experience includes acting as an adviser to the German automobile industry in the German Federal Ministry of Economics and as a strategy consultant for international enterprises. He is also a scientific director at the Institute for Regulation and Governance in Bonn, Germany.

Thomas Neifer is a research associate at the University of Siegen, Germany, and the Bonn-Rhein-Sieg University, Germany. His academic background is in innovation, information management, and consumer informatics. He conducts research on recommendation and reputation mechanisms in the context of sustainable food consumption and mobility. As a lecturer, he teaches operations research, data science, statistics, and economics.