Department of Industrial Engineering & Operations Research

IEOR 162: Linear Programming (Spring 2014)

Class time & locationLecture: MW 9-10A, 150 GSPPDiscussion: F 9-10A, 150 GSPP or F 10-11A, 3107 ETCHEVERRY

InstructorProfessor Dorit S. HochbaumE-mail: hochbaum@ieor.berkeley.eduOffice Hours: Th 2-3P, 4181 ETCHEVERRY

Graduate student instructorAuyon SiddiqE-mail: auyon.siddiq@berkeley.eduOffice Hours: Wed 1-3P, 4176 ETCHEVERRY

Course web page: bSpace

Required text: Introduction to Mathematical Programming Applications and Algorithms. 4th Edition,Winston and Venkataramanan, Duxbury Press, 2003. (ISBN 0-534-35964-7)

Recommended reference: AMPL: A Modeling Language for Mathematical Programming. 2nd Edition,Fourer, et. al., Duxbury Press, 2002. (ISBN 0-534-38809-4)

Course description:This course introduces the students to quantitative modeling and formulation of optimization problems. Thetechnique of solving linear programming problems using the simplex algorithm will be described in detail.The extent and usability of that technique and of linear programming modeling will be discussed along withalternative quantitative approaches. The course also discusses techniques for solving network flow problemsand linear integer programming problems.

Homeworks:Homework will be assigned on a weekly basis on Wednesdays and are due on Friday of the following weekat the beginning of discussion (so you have 10 days per assignment). Working in groups is encouraged, buteach student must submit their solutions independently. The two lowest homework grades will be dropped.Late homework will not be accepted.

Project:There will be a project consisting of modeling and computational solution to problems (groups of 3 or 4). De-tails of the project will be given out mid-way through the semester. The due date of the project is May 5th.

Grading:Homework 15%Project 10%Midterm 30%Final 45%

Tentative course schedule:

Lecture Topic Reading Date

1 Introduction Ch. 1 Jan 222-4 Formulation and applications of linear programming Ch. 3.1, 3.3-3.12 Jan 27, 29, Feb 35-8 Graphical solutions and sensitivity in two-dimensions Ch. 3.2, 5.1 Feb 5, 10, 12, 199 Interpretting the output of optimization software Ch. 5.2 Feb 2410-12 The simplex algorithm Ch. 4 Feb 26, Mar 3, 513-15 Sensitivity analysis Ch. 5, 6.1-6.4 Mar 10, 12, 1716 Midterm Mar 1916-17 Duality Ch 6.5 - 6.10 Mar 31, Apr 218 Intro to integer-linear programming Ch. 9.1 Apr 719-20 Formulation and applications of ILP Ch. 9.2 Apr 9, 1421 Branch-and-bound algorithm, dual simplex method Ch. 9.3-9.4, 6.11 Apr 1622 Cutting plane algorithms Ch. 9.8 Apr 2123-26 Network problems Ch 8.1-8.6 Apr 23, 28, 30, May 5

Project deadline May 527 Miscellaneous topics and course overview May 7

Final exam May 12 (7-10P)