INTRODUCTION TO LINEAR OPTIMIZATION BY DIMITRIS BERTSIMAS PDF

I have been MIT faculty since My research interests include optimization, machine learning and applied probability and their applications in health care, finance, operations management and transportation. I have co-authored more than scientific papers and four graduate level textbooks. I am also a member of the National Academy of Engineering since , an INFORMS fellow, and have received numerous research awards including the Morse prize , the Pierskalla award for best paper in health care , the best paper award in Transportation , the Farkas prize , the Erlang prize , the SIAM prize in optimization , the Bodossaki prize and the Presidential Young Investigator award I have consulted widely in a variety of industries and have cofounded several very successful companies. In , the assets of Dynamic Ideas were sold to American Express.

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Complexity and the Ellipsoid Method 8. Interior Point Methods Integer Programming We end with a brief introduction to Semidefinite Programming The sections to be covered in each lecture are listed below. Please read these before coming to class. Grading: There will be weekly homework sets and a midterm exam in-class.

The midterm covers Chapters 1,2,3,4. The final is a term paper take-home. Homework: There will be a weekly homework assignment, to be handed in on Tuesdays at am, at the end of class. Late homework will not be accepted. No exceptions. The assignments, posted below, refer to the text book.

No homework after spring break, so you can focus on your term paper. Midterm Exam: The midterm covers the first four chapters and is held in class on Thursday, March 2. This is an open book exam. The exam and solutions are posted here. Final Exam: You will write a term paper on a topic of their choice related to the class.

This can focus on foundational mathematics e. Your choice. You may work on this by yourself or in teams of two.

Please submit a proposal for your project by Thursday, March This should fit on one page and contain: names of author s , title, sources, and a brief description. The final version of the paper is due on Thursday, May Student Presentations: Short talks on the term papers are scheduled for April 24,25,26, Click here for the schedule. Registered students are expected to attend all lectures.

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Dimitris Bertsimas

Dynamic Ideas , Belmont, Massachusetts, The Analytics Edge provides a unified, insightful, modern and entertaining treatment of analytics. The book covers the science of using data to build models, improve decisions, and ultimately add value to institutions and individuals. The book is a modern and unified introduction to linear optimization linear programming, network flows and integer programming at the PhD level. It covers, in addition to the classical material, all the recent developments in the field in the last ten years including the development of interior points, large scale optimization models and algorithms and complexity of linear optimization. It emphasizes the underlying geometry, intuition and applications of large scale systems. This book represents a departure from existing textbooks.

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Introduction to Linear Optimization

A faculty member since , his research interests include optimization, stochastic systems, machine learning, and their application. In recent years, he has worked in robust optimization, statistics, healthcare, transportation and finance. Bertsimas was a cofounder of Dynamic Ideas, LLC, which developed portfolio management tools for asset management. In , the assets of Dynamic Ideas were sold to American Express.

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