Decision Science is the discipline that is concerned with the development and applications of quantitative methods and techniques to support decision making processes. This book discusses the general principles of often used optimisation techniques such as Linear Programming, Integer Programming, Dynamic Programming, Non-linear Programming, Network Theory and Simulation. It aims to fill the gap between theory and practice. It especially discusses the theoretical background of important quantita…
Decision Science is the discipline that is concerned with the development and applications of quantitative methods and techniques to support decision making processes. This book discusses the general principles of often used optimisation techniques such as Linear Programming, Integer Programming, Dynamic Programming, Non-linear Programming, Network Theory and Simulation. It aims to fill the gap between theory and practice. It especially discusses the theoretical background of important quantitative methods and techniques as well as how they can be applied to practical decision making problems. Therefore the modelling process is illustrated with examples of corporate firms, consumers, governments and other non-profit organizations. Decision science: theory and application is a thoroughly revised edition of two former Dutch versions. The authors have used their extensive didactical experience to find a proper balance between mathematical exactness, knowledge and readability on the one hand and understanding, insights and applicability of the subjects on the other hand. Virtually every topic in the text is illustrated by small, class-tested, numerical examples, exercises and graphical illustrations. This edition contains more than 160 figures. The book is therefore an elemental asset in introductory courses on decision science. It is addressed to undergraduates, postgraduates and research students.
Decision Science is the discipline that is concerned with the development and applications of quantitative methods and techniques to support decision making processes. This book discusses the general principles of often used optimisation techniques such as Linear Programming, Integer Programming, Dynamic Programming, Non-linear Programming, Network Theory and Simulation. It aims to fill the gap between theory and practice. It especially discusses the theoretical background of important quantitative methods and techniques as well as how they can be applied to practical decision making problems. Therefore the modelling process is illustrated with examples of corporate firms, consumers, governments and other non-profit organizations. Decision science: theory and application is a thoroughly revised edition of two former Dutch versions. The authors have used their extensive didactical experience to find a proper balance between mathematical exactness, knowledge and readability on the one hand and understanding, insights and applicability of the subjects on the other hand. Virtually every topic in the text is illustrated by small, class-tested, numerical examples, exercises and graphical illustrations. This edition contains more than 160 figures. The book is therefore an elemental asset in introductory courses on decision science. It is addressed to undergraduates, postgraduates and research students.
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