Models And Methods For Management Science


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Models and Methods for Management Science


Models and Methods for Management Science

Author: Hao Zhang

language: en

Publisher: Springer Nature

Release Date: 2022-08-18


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This textbook introduces systems science as an entry point to present a basic introduction to research models and methods in management science (operation research). This textbook selects the classic quantitative models and methods as well as rich cases and detailed examples, which are suitable for students with a certain management and economics knowledge for further study, and helps to develop the abilities of using the basic models in real life.

Business Analytics with Management Science Models and Methods


Business Analytics with Management Science Models and Methods

Author: Arben Asllani

language: en

Publisher: FT Press

Release Date: 2014-11-17


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Master decision modeling and analytics through realistic examples, intuitive explanations, and tested Excel templates. Business Analytics with Management Science has been designed to help students, practitioners and managers use business analytics to improve decision-making systems. Unlike previous books, it emphasizes the application of practical management science techniques in business analytics. Drawing on 20+ years of teaching and consulting experience, Dr. Arben Asllani introduces decision analytics through realistic examples and intuitive explanations – not complex formulae and theoretical definitions. Throughout, Asllani helps practitioners focus more on the crucial input-output aspects of decision making – and less upon internal model complexities that can usually be "delegated" to software.

Data, Models, and Decisions


Data, Models, and Decisions

Author: Dimitris Bertsimas

language: en

Publisher: Ingram

Release Date: 2004


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Combines topics from two traditionally distinct quantitative subjects, probability/statistics and management science/optimization, in a unified treatment of quantitative methods and models for management. Stresses those fundamental concepts that are most important for the practical analysis of management decisions: modeling and evaluating uncertainty explicitly, understanding the dynamic nature of decision-making, using historical data and limited information effectively, simulating complex systems, and allocating scarce resources optimally.