| IE53500 - Linear ProgrammingFall 2018 Days:
TBA TBACredit Hours:
As a beginning graduate course, the first goal is to teach the students the skills to formulate real-world problems as linear programs, and solve them using the available software. The second goal is to teach the students the theoretical principles of linear optimization. Description:
Linear programming problems arise pervasively in science and engineering. The students will be taught to use the available linear programming software to solve real world problems. They will also obtain a broad exposure to the theoretical underpinnings of linear optimization. Prior exposure to optimization is not necessary. Topics Covered:
Introduction; classification of optimization problems; formulation of linear and integer programs; using available software to solve linear programs; geometry of 2-dimensional linear programs; Simplex method: basic feasible solutions, pivoting, degeneracy, cycling and anti-cycling pivot rules, phase I and phase II algorithms; duality; sensitivity analysis; introduction to computational complexity; ellipsoid method; interior point methods; network flow problems.Prerequisites:
Linear algebraWeb Address:http://www.itap.purdue.edu/learning/tools/blackboard/Homework:
Six to eight assignments, assigned roughly every two weeks, may be downloaded from the course web page; the assignments will count for approximately 50% of the course grade.Exams:
Two midterm exams worth approximately 25% of the course grade each. There will be no final exam.Textbooks:
Disclaimer: final textbook listings are available in April for fall and summer semesters. Please visit the Listing of Textbooks by College or School for the most up-to-date information.
Recommended: Introduction to Mathematical Programming: Applications and Algorithms, Volume 1; Wayne L. Winston and Munirpallam Venkataramanan, Duxbury Press, 4th edition, 2002..
Recommended: Linear Programming 1: Introduction (v.1) by George B. Dantzig and Mukund N. Thapa, Springer Series in Operations Research and Financial Engineering, 1997.
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