Optimization in Intelligent Systems
- Department of Control Engineering
The goal is to show the algorithms for several combinatorial optimization problems. Following the subject on algorithms, we show optimisation techniques based on graphs, integer linear programming, heuristics, approximation algorithms and state space search methods. We focus on application of optimization in stores, ground transport, flight transport, logistics, planning of human resources, scheduling in production lines, message routing, scheduling in parallel computers.
- Syllabus of lectures:
1. Example Applications and Formulation of Problems.
2. Basic Terms of Graph Theory.
3. Spanning Trees.
4. Network Flows.
5. Linear Programming.
6. Algorithms for Linear Programming. Test I.
7. Time Complexity of Algorithms.
8. Branch and Bound Technique and its Applications
9. Metaheuristics and Approximation Algorithms.
10. Scheduling on Monoprocessor
11. Scheduling on Parallel Processors
12. The Job Shop Problem
- Syllabus of tutorials:
1. Introduction to the Scheduling Toolbox.
2. Properties of Graphs.
3. Spanning Tree and Clustering.
4. Individual Projects - Topics.
5. Applications of Network Flows
6. Linear Programming
7. Scheduling and Branch and Bound Technique
8. Approximation Algorithms and the SAT Problem
9. Individual Projects - Defense of the Programs
10. Test II.
11. Individual Projects - Defense.
- Study Objective:
- Study materials:
 B. H. Korte and J. Vygen, Combinatorial Optimization: Theory and Algorithms. Springer, third ed., 2006.
Some parts of:
 J. Demel, Grafy a jejich aplikace. Academia, second ed., 2002.
 J. Blazevicz, Scheduling Computer and Manufacturing Processes. Springer, second ed., 2001.
- Further information:
- No time-table has been prepared for this course
- The course is a part of the following study plans: