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September, 03 2019

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September, 10 2019

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Applied Optimalization

The aim of the course is to acquaint students with the methods of optimization and their application in operations research. Students will become familiar with the formulation of a number of real problems leading to linear, integer and nonlinear programming - it eg. On problems of the scheduling process, transport and logistics, production management, effectiveness evaluation (DEA) classification and data mining, portfolio management, statistical processing data from other areas. Get acquainted with basic methods for solving optimization problems thus formulated, both methods are precise, and with the heuristic. They also get an overview of available optimization solver.

What are you going to learn

  1. Optimization problems - formulation of optimization problems
  2. Optimizing - Continuous vs. discrete optimization, linear vs. nonlinear problems, multiobjective problems
  3. Use Cases - Problems in the transportation and logistics variations TSP
  4. Working with processes - scheduling and process management, job scheduling
  5. Application to financial standing analysis - Financial application portfolio management
  6. DEA - DEA and effectiveness evaluation
  7. Data mining - Applications of classification, data analysis, data mining in
  8. Basic optimization algorithms - Overview of algorithms for linear, nonlinear and discrete programming
  9. Heuristic methods - Heuristic and metaheuristické methods for difficult optimization problems
  10. Modeling - modeling languages, solvers, numerical problems, implementation issues
  11. Computational complexity of optimization - computational complexity of optimization problems

How the course is organized

Full time study

The course consist of 6 lectures and 12 seminars, each lasting 1,5 hours.

Part time study

The course is taught only in full time study form for part time students.

Recommended literature

  • Carter, M. W., Price, C.C.: Operations Research. A Practical Introduction. CRC Press, 2000
  • Schrijver, A.: Theory of Linear and Integer Programming. Wiley, 2000
  • Bertsekas, D. P.: Nonlinear Programming. Athena Scientific, 2008
  • Nemhauser, G. L., Wolsey, A. L.: Integer and Combinatorial Optimization. Wiley, 1999
  • Luenberger, D. G., Ye, Y.: Linear and Nonlinear Programming. Springer, 2008h