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[ 926LOMACLOS14 ] SE Computational Logistics: Optimization
Versionsauswahl
(*) Unfortunately this information is not available in english.
Workload Education level Study areas Responsible person Hours per week Coordinating university
6 ECTS M2 - Master's programme 2. year Business Administration Sophie Parragh 2 hpw Johannes Kepler University Linz
Detailed information
Pre-requisites (*)KS Operations Research und IK Operations Research
Original study plan Master's programme Business Informatics 2020W
Objectives Students have competent knowledge of existing exact solution concepts used in logistics applications. They know the modelling concepts of mixed integer programming. They are able to design mixed integer programs for logistics applications on their own and to design, implement and test appropriate optimization techniques, interfacing with commercial solver tools. They also know how to evaluate and validate the obtained results.
Subject Modelling of mixed integer programs for logistics applications, branch and bound, branch and cut, column generation, branch and price.
Criteria for evaluation Talk on the project thesis, exam
Methods exercises, project thesis
Language English
Study material Suhl, Mellouli: Optimierungssysteme, Springer, 2006.

Grünert, Irnich: Optimierung im Transport, Band I, Grundlagen, Shaker Verlag, 2005.

Korte, Vygen: Combinatorial Optimization - Theory and Algorithms, 5th Edition. Springer, 2010.

Desaulniers, Desrosiers, Solomon: Column Generation, Springer, 2005.

Additional material will be announced during class.

Changing subject? No
Earlier variants They also cover the requirements of the curriculum (from - to)
2WCLOOP: SE Computational Logistics: Optimization (2013S-2014S)
On-site course
Maximum number of participants 25
Assignment procedure Assignment according to priority