دانلود کتاب مدلسازی بهینه سازی با استفاده از R

This book covers using R for doing optimization, a key area of operations research, which has been applied to virtually every industry. The focus is on linear and mixed integer optimization. Pedagogically, since the late 1990s, I had been a proponent of teaching intro- ductory optimization using spreadsheets as a way to bridge the barrier be- tween data and applications as well as teaching better spreadsheet practices. While this worked well, the disconnect with algebraic modeling was always a problem. Excel add-ins enabling algebraic tools were rich but not seamless. In 2018, I decided to switch to R for a variety of reasons: • With the rapid rise of interest in data analytics, it became important to introduce a data analytics platform. • Working technology and business professionals should have an awareness of the tools and language of data analysis to deal with consultants, data scientists, and others. • New software and extensions reduced the barrier to entry for people to start using data analytics tools. Philosophically, the book emphasizes creating formulations before going into implementation. This is important for the following reasons: • Reading the literature is based on the algebraic representation. • An algebraic representation allows for clear understanding and generaliza- tion of large applications. • Writing formulations is necessary to explain and convey the modeling de- cisions made. • Becoming proficient in the mathematical language used will be transferable to other analytical models. • Dividing the modeling stage from the implementation enables better de- bugging of models avoids what is sometimes referred to as spaghetti code in programming. • Separating enables the reader to readily transition to another language for implementation in the future (ex. Python, Julia, AMPL, GAMS) with what will seem like little more than a dialect change.