DM841 - Heuristics and Constraint Programming for Discrete Optimization

Schedule

... see timetable
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Man, 08-10I (Fælles)
(IMADA Seminarrum)
I (Fælles)
(IMADA Seminarrum)
I (Fælles)
(IMADA Seminarrum)
Man, 12-14I (Fælles)
(U49B)
Tir, 12-14I (Fælles)
(IMADA Seminarrum)
I (Fælles)
(IMADA Seminarrum)
Tir, 14-16I (Fælles)
(IMADA Seminarrum)
I (Fælles)
(IMADA Seminarrum)
I (Fælles)
(IMADA Seminarrum)
I (Fælles)
(IMADA Seminarrum)
I (Fælles)
(IMADA Seminarrum)
I (Fælles)
(IMADA Seminarrum)
I (Fælles)
(IMADA Seminarrum)
Ons, 10-12I (Fælles)
(IMADA Seminarrum)
I (Fælles)
(IMADA Seminarrum)
I (Fælles)
(IMADA Seminarrum)
I (Fælles)
(IMADA Seminarrum)
I (Fælles)
(IMADA Seminarrum)
I (Fælles)
(IMADA Seminarrum)
I (Fælles)
(IMADA Seminarrum)
I (Fælles)
(IMADA Seminarrum)
I (Fælles)
(IMADA Seminarrum)
Tor, 08-10I (Fælles)
(IMADA Seminarrum)
I (Fælles)
(IMADA Seminarrum)
Fre, 08-10I (Fælles)
(IMADA Seminarrum)
I (Fælles)
(IMADA Seminarrum)
I (Fælles)
(IMADA Seminarrum)
I (Fælles)
(IMADA Seminarrum)
I (Fælles)
(IMADA Seminarrum)
I (Fælles)
(IMADA Seminarrum)
I (Fælles)
(IMADA Seminarrum)
I (Fælles)
(U49E)
I (Fælles)
(IMADA Seminarrum)
I (Fælles)
(IMADA Seminarrum)
I (Fælles)
(IMADA Seminarrum)
I (Fælles)
(IMADA Seminarrum)
I (Fælles)
(IMADA Seminarrum)

You can import the schedule in your calendar using the iCalendar file at this URL

Introductory Classes

Local Search Part

DateTopic and SlidesLiterature and Assignments
026.05Presentation
101.09Course introduction, Motivations, Combinatorial Optimization, Methods[MAK, appA,B] [ Review ]
202.09Solution methods. SAT[HM, ch 1,2] [L1; RN] [V1]
305.09Local Search and Metaheuristics[HM, ch 2]
408.09C++ Review[S] [L4] [ Code ]
509.09Local Search in EasyLocal++[DS]
T110.09Bus Driver Example[ Code ]
T215.09Practice
618.09Local Search: Iterative Improvement and Runners[HM, ch 2; HS ch 2]
T319.09Practice
723.09Stochastic Local Search and Metaheuristics[HM, ch 2; HS ch 2]
825.09Simulated Annealing[RBW ch5] [MAK ch 7]
926.09Tabu Search (see lec 8). Working Environment[MAK ch 7]
1029.09Variable Neighborhood Search (see lec 8). Experimental analysis[HaMl] [ ObAss1 ]
1101.10Experimental analysis (see lec 10)
T403.10Q&A. Efficiency issues in SAT[ ObAss2 ]
1207.10SMTWT. Efficiency issues. Neighborhoods and Landscapes
1322.10Examples: Binary Programming, TSP, Steiner Tree, Parallel Machines, Graph Coloring[ ObAss3 ]
1424.10Evolutionary Algorithms. Midway Evaluation

Constraint Programming Part

DateTopic and SlidesLiterature and Assignments
129.10Introduction to Constraint Programming[L5]
231.10Example and Installation issues in Gecode[ Gecode ] [MPG, Ch 1,2,3]
305.11Solving CSPs - Overview
407.11Introduction to Gecode
512.11Global Constraints[MPG, ch 4; HK sc. 7.1-7.2] [R sc. 1-2]
T114.11Global Constraints and Modeling exercises[VH ch 2-4] [ ObAss1 ]
T219.11More on Global Constraints and Examples[MPG, ch 4, 7.4] [MPG ch 16] [LC]
621.11Notions of local consistency[B] [ Rosetta ] [MPG ch 18, Video ] [ C++ Video ] [CHOP]
725.11Constraint propagation algorithms for AC[B] [Ba]
828.11Exercises. Constraint Propagation Algorithms for AC[B] [Ba]
902.12Further notions of local consistency[B] [SC]
1003.12Propagation Events and Gecode Implementation[B] [SC] [MPG ch. 22,23,24,25,26]
1105.12Filtering algorithms for global constraints[HK], [VH, ch 8]
T308.12Exercises[ ObAss2 ]
T409.12More Filtering Algorithms (slides lec 11)[HK]
1212.12Search[RBW, ch 4 (in BB)] [SC] [MPG, ch 8,9] [VH, ch 9-10]
1316.12Set Variables[MPG, ch 5, 6] [VH, ch 6,7]
1417.12Symmetry breaking[GPP] [VH, ch 5]
T419.12Finishing previous lectures + ObAss2[ ObAss3 ]

Course Material

Literature

No textbook is required. The following books are recommended.

Main books:

Other references

Books

Chapters and articles:

Animations, Visualizations, Games

Evaluation

  • Ordinary exam: During the course there will be mandatory assignments. The final grade will be given by a weighted average of the grades received in the assignments.
  • Re-exam: it consists of a single project corresponding in size to the multiple assignments during the course.

Examples of past LS projects:

Course Evaluation by Students

Date: 2015-01-30T16:09+0100

Author: marco

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