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This book is based on the lecture notes of the author delivered to
the students at the Institute of Science, Banaras Hindu University,
India. It covers simplex, revised simplex, two-phase method,
duality, dual simplex, complementary slackness, transportation and
assignment problems with good number of examples, clear proofs,
MATLAB codes and homework problems. The book will be useful for
both students and practitioners.
This book discusses unconstrained optimization with R-a free,
open-source computing environment, which works on several
platforms, including Windows, Linux, and macOS. The book highlights
methods such as the steepest descent method, Newton method,
conjugate direction method, conjugate gradient methods,
quasi-Newton methods, rank one correction formula, DFP method, BFGS
method and their algorithms, convergence analysis, and proofs. Each
method is accompanied by worked examples and R scripts. To help
readers apply these methods in real-world situations, the book
features a set of exercises at the end of each chapter. Primarily
intended for graduate students of applied mathematics, operations
research and statistics, it is also useful for students of
mathematics, engineering, management, economics, and agriculture.
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