Using real-life applications, this graduate-level textbook introduces different mathematical methods of scientific computation to solve minimization problems using examples ranging from locating an aircraft, finding the best time to replace a computer, analyzing developments on the stock market, and constructing phylogenetic trees. The textbook focuses on several methods, including nonlinear least squares with confidence analysis, singular value decomposition, best basis, dynamic programming, linear programming, and various optimization procedures. Each chapter solves several realistic problems, introducing the modelling optimization techniques and simulation as required. This allows readers to see how the methods are put to use, making it easier to grasp the basic ideas. There are also worked examples, practical notes, and background materials to help the reader understand the topics covered. Interactive exercises are available at www.cambridge.org/9780521849890.

'… this book will help students understand methods in some of their appropriate contexts, in a relatively easy, fresh, and concise way.'

E. Vavalis Source: Computing Reviews

'… the text makes an important contribution: it describes the thought process necessary to solve a problem computationally, considers the various possible models, and shows which ones lead to the most precise solutions. I recommend this text for instructors who are interested in problem-based or other interactive learning styles.'

Source: Physics Today