This course is designed to provide students with a thorough understanding of concepts and methods for several important classes of Linear Programming (LP) and Network Flow problems, as well as the implementation and testing of these methods in software.

Lecture 1 | Introduction, Review of Linear Algebra, Convex Analysis| Lecture_1  hw1  ece6108_solutions_hw1

Lecture 2 | Linear Programming and Revised Simplex |  Lecture_2  hw2  ece6108_solutions_hw2

Lecture 3 | Basis updates, Storage Schemes, Dantzig-Wolfe Decomposition |  Lecture_3  hw3 ece6108_solutions_hw3

Lecture 4 | Duality | Lecture_4 hw4 ece6108_solutions_hw4

Lecture 5 | Dual Simplex, Primal – Dual And Karmarkar’s Algorithms | Lecture_5 hw5 ece6108_solutions_hw5

Lecture 6 | Shortest Path Algorithms (Part I) | Lecture_6

Lecture 7 | Shortest Path Algorithms (Part II) | Lecture_7   hw6  ece6108_solutions_hw6

Lecture 8 | Assignment Algorithms| Lecture_8 midterm

Lecture 9 | Maximum Flow in a Network |    Lecture_9

Lecture 10 | Minimum Cost Network Flows | Lecture_10

Lecture 11 | Minimum Spanning Trees & Cone Programming | Lecture_11   hw7

Lecture 12 | Knapsack Problems | Lecture_12

ece6108_course_outline

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