Lecture22

# Lecture22 - Advanced Operations Research Techniques IE316...

This preview shows pages 1–5. Sign up to view the full content.

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
This is the end of the preview. Sign up to access the rest of the document.

Unformatted text preview: Advanced Operations Research Techniques IE316 Lecture 22 Dr. Ted Ralphs IE316 Lecture 22 1 Reading for This Lecture • Bertsimas Sections 10.2, 10.3, 11.1, 11.2 IE316 Lecture 22 2 Branch and Bound • Branch and bound is the most commonly-used algorithm for solving MILPs. • It is a divide and conquer approach. • Suppose F is the feasible region for some MILP and we wish to solve min x ∈ F c T x . • Consider a partition of F into subsets F 1 ,...F k . Then min x ∈ F c T x = min { 1 ≤ i ≤ k } { min x ∈ F i c T x } . • In other words, we can optimize over each subset separately. • Idea : If we can’t solve the original problem directly, we might be able to solve the smaller subproblems recursively. • Dividing the original problem into subproblems is called branching . • Taken to the extreme, this scheme is equivalent to complete enumeration. IE316 Lecture 22 3 Branch and Bound • Next, we discuss the role of bounding . • For the rest of the lecture, assume all variables have finite upper and lower bounds....
View Full Document

{[ snackBarMessage ]}

### Page1 / 9

Lecture22 - Advanced Operations Research Techniques IE316...

This preview shows document pages 1 - 5. Sign up to view the full document.

View Full Document
Ask a homework question - tutors are online