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Features simple treatment of uncertain linear programming. This book also presents an analysis of the interconnections between the construction of appropriate uncertainty sets and the classical chance constraints (probabilistic) approach.
The 5th edition of Model Building in Mathematical Programming discusses the general principles of model building in mathematical programming and demonstrates how they can be applied by using several simplified but practical problems from widely different contexts.
Algorithms are a dominant force in modern culture, and every indication is that they will become more pervasive, not less. The best algorithms are undergirded by beautiful... Læs mere
Widely known as the father of linear programming, George B. Dantzig has been a major influence in mathematics, operations research and economics. This volume highlights the... Læs mere
This book provides a clear understanding regarding the fundamentals of matrix and determinant from introduction to its real-life applications.
This book introduces linear transformation and its key results which have applications in engineering, physics, and various branches of mathematics. Linear... Læs mere
Students will learn how to apply mathematics to practical real-life questions in business, economics, and the social sciences by modelling linear... Læs mere
Students will learn how to apply mathematics to practical real-life questions in business, economics, and the social sciences by modelling linear... Læs mere
This book is for beginners who are struggling to understand and optimize non-linear problems. The content will help readers gain an understanding and learn how to formulate real-world problems and will also give insight to many researchers for their future prospects.