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Lagrangean relaxation for integer programming. Download the following
tutorial.
The lecture notes are here. Review
of primal and dual simplex methods, with emphasis on re-optimization after the
addition of violated cuts.
General --
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Syllabus --
Textbook --
Class Notes --
Homework --
Grading--
Exam--
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Projects --
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Historical perspectives
Department of OPIM
OPIM-916: Advanced Integer Programming
Spring 2007, Tuesdays & Thursdays 4:30-6:00 PM, 260, JMHH
Professor Monique Guignard-Spielberg
New this week
Exam Period (starting April 26).
The exam is available
here. Please send me an email when you pick it up and another one when you return it.
Don't forget to return the
"no cheating" form at the same time as the exam.
The project report is due at the latest May 4.
Both the exam and the report must be returned to one of the secretaries in the OPIM Department.
Week of April 16.
Homework 5 is posted. Due on 4/24 (day of class presentations).
Project presentations: 5-7 pm, Tuesday April 24, room TBA.
Week of April 9.
Makeup class on 4/11 in room TBA.
Please download the following
gams code
and
gams listing
showing how to do column generation for the cutting stock problem,
as well as a
gams code and
gams listing
showing how to do column generation for the strong Lagrangean relaxation of the GAP
and the put file with results.
The data set is here.
For more information on the cutting stock problem, go to
wikipedia
or the Argonne Lab page
or on Erwin's page.
Finally if you want a more visual introduction to this problem, click on
this,
solve your own problem online, and "view" the answer!
The following link is presenting
Benders algorithm in a gams context.
Week of April 2.
Makeup class on 4/04 in room F86
HW4 is available.
Recommended reading:
slides by Vanderbeck (Univ. of Bordeaux, France).
Gomory for OR Hall of Fame
Balas for OR Hall of Fame
Week of March 26.
Makeup class on 3/28 in room F38
Week of March 4.
Makeup class on 4/04 in room F86
HW4 is available.
Spring break and following week: no classes, but... you may want to look at these sites,
either for your project or for additional learning!
global optimization .
teaching the TSP.
Week of February 26
Week of February 19
Week of February 12
Week of February 5
Week of January 29
Additional readings: download from Discrete Mathematics, Volume 306, Issues 10-11 , 28 May 2006, Pages 886-904.
This is a reprint of the 1973 paper by Chvatal.
Week of January 15
Additional readings: paper in T.O.P.
and
paper by Geoffrion.
Course Description
Many optimization models include either integer or 0-1 decision variables. The
integrality requirements make the problems much harder to solve than the
corresponding continuous optimization problems. The course will provide
students with a variety of analytical and algorithmic tools for approaching
such hard problems. Emphasis will be on modeling, as well as on approximate
(heuristic), and exact (iterative and enumerative) methods.
Prof. Monique Guignard-Spielberg
Office: 569 JMHH
Phone: 215-898-8235
Email: monique_guignard at yahoo.com
URL: http://opim-sun.wharton.upenn.edu/~guignard
Office Hours: Tuesday, 1:30 to 2:45 p.m.
The
textbook used is “Integer Programming”, by L. Wolsey, Wiley, 1998.
Additional
reading material will be distributed during the semester.
List of topics to be covered:
Course overview. Examples of problems with large integrality gaps, and with feasible rounded solutions yielding large relative gaps
Review
of LP duality, (January 9)
and of the primal and dual simplex methods, with emphasis on re-optimization after the
addition of violated cuts.
Branch-and-bound
and enumeration (January 9)
. Driebeck penalties.
0-1 knapsack problems. Their LP solutions. BB. Cover inequalities.(January 23)
The simplex method with upper bounds.
(January 25)
LP duality and the Lagrangean function.
For this section, download the following
tutorial.
Primal relaxation and Lagrangean relaxation, geometric interpretation, integrality property.
Integer linearization property, application to the capacitated p-median problem.
Analysis of Lagrangean relaxation schemes and quality of bounds from the viewpoint of the geometric interpretation.
Application to the GAP and review of all possible constraint dualizations.
Integer linearization property for the capacitated facility location problem when the demand constraint is dualized.
The bi-knapsack problem. Construction of the Lagrangean function for the total Lagrangean relaxation. Integrality property.
Properties of the Lagrangean function. Examples. Contours, subgradient method.
Dantzig-and-Wolfe decomposition algorithm, solution of the Lagrangean dual by column
generation: example of the multi-item capacitated lotsizing problem and the GAP.
Extensions of Lagrangean relaxation: Lagrangean decomposition and substitutions. Examples.
Valid inequalities. Chvatal-Gomory procedure.
Linear
programming relaxation and Gomory cuts for pure (February xx) and mixed-integer problems.
Lifting, covers, lifted covers. (February xx)
Modeling integer programming problems: choice
of decision variables and of constraints, simple strengthening
techniques. Examples: SPLP, CPLP,
lotsizing, with and without disaggregation.
Integrality gaps. Model tightening (see paper).
(February xx)
Variable fixing, cliques and implication tables, probing. note to read (February xx)
Total unimodularity. Relationship with integer feasible solutions for integer programming problems. Special cases of network flow problems. (February xx, March xx)
Benders partitioning for mixed-integer
problems (March xx). Examples. Initialization.
Gams coverage of Benders.
Benders inequalities of types I and II, obtained from simplex tableau
( March xx)
and their use outside of the partitioning algorithm (March xx) . Special examples with and without dual extreme rays. (March xx).
Relaxations. Surrogate
relaxation and surrogate duals (March xx, xx, xx).
Convex nondifferentiable functions and subgradients.
(March xx).
Applications:
airline crew scheduling, lotsizing, facility location, production scheduling... (throughout the semester).
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