Course detail
Optimization Models II
FSI-SO2-A Acad. year: 2025/2026 Summer semester
The course focuses on advanced optimization models and methods of solving problems in logistics and related engineering problems. It includes foundations of stochastic programming (deterministic reformulations, theoretical properties, and selected algorithms for one stage and basic two stage problems) with applications in logistics. The course also includes introductory information on the principles of modification and generalization of advanced optimization models (integer programs), which are further extended and deepened in the follow-up courses. The course was compiled on the basis of the author's experience with similar courses at foreign universities.
Language of instruction
English
Number of ECTS credits
4
Supervisor
Department
Entry knowledge
The presented topics require basic knowledge of optimization concepts. Standard knowledge of probabilistic and statistical concepts is assumed.
Rules for evaluation and completion of the course
There is an exam based on presentation of a written paper accompanied by oral discussion of results. Formulation, calculation and theoretical aspects of the work are evaluated. The related themes are based on logistic applications of model properties, bounds, and approximations, modified and addvanced reformulations, etc. The attendance at seminars is required as well as active participation. Passive or missing students are required to work out additional assignments.
Aims
The course objective is to develop the advanced knowledge of sophisticated optimization techniques as well as the understanding and applicability of principal concepts. The course is mainly designated for students of logistics, however it might be useful for applied sciences and engineering students as well. Students will learn of the recent topics in advanced optimization modelling and related optimization algorithms. They will also develop their ideas about suitable models for typical applications.
The study programmes with the given course
Programme N-LAN-A: Logistics Analytics, Master's, compulsory
Type of course unit
Lecture
26 hours, optionally
Syllabus
1.-2. Integer programming and selected models in logistics.
3.-4. Advanced integer programming (indicator variables) models, their properties and basic ideas of solution methods.
5.-6. Underlying mathematical program and selected applications. WS and HN approach. IS and EV reformulations. EO, EEV, EVPI and VSS. Deterministic
7.-8. MM and VO, the solution of the large problems in logistics. Multicriteria optimization.
9.-10. PO and QO, relation to integer programming. Probabilistic constraints.
11.-12. The use of recourse.
13. Advanced applications of mathematical programming.
Computer-assisted exercise
13 hours, compulsory
Syllabus
Logistic examples and exercises on:
1.-2. Integer programming and selected models in logistics.
3.-4. Advanced integer programming (indicator variables) models, their properties and basic ideas of solution methods.
5.-6. Underlying mathematical program and selected applications. WS and HN approach. IS and EV reformulations. EO, EEV, EVPI and VSS. Deterministic
7.-8. MM and VO, the solution of the large problems in logistics. Multicriteria optimization.
9.-10. PO and QO, relation to integer programming. Probabilistic constraints.
11.-12. The use of recourse.
13. Advanced applications of mathematical programming.
Course participance is obligatory.