Objectives and competences
Students:
are farmiliarized with and study the basics for managing logistics systems using quantitative methods,
understand the concept of operational research and develop problem solving skills in logistics systems using the linear and whole number linear model,
develop the skills to interpret the gained results,
learn how to improve the solution based on the chosed criteria.
Content (Syllabus outline)
• Systems of linear equations and inequations (revision of solving linear equations using Gauss elimination method and matrix equations, solving systems of linear inequations using the graphic method),
• convex sets and determining extreme points,
• linear programming (problem formulation, solving problems using graphical method, solving problems using LINGO and Microsoft Excel software, sensitivity analysis of the solution);
• integer linear programming,
• basics of graph theory (transforming transhipment, assignment, maximum flow, etc. to linear optimization problems),
• DEA (Data Envelopment Analysis),
• AHP (Analitical Hierarchy Process) method.
Learning and teaching methods
Lectures: students understand the theoretical frameworks of the course (used methods of explanation, demonstration and conversation). Part of the lecture course is in a classroom while the rest is in the form of e-learning (e-lectures may be given via video-conferencing or with the help of specially designed e-material in a virtual electronic learning environment). At e-lectures students are also faced with independent and problem-based learning, where they solve open problems.
Students enhance their theoretical knowledge and are able to apply it. Part of the seminar is in a classroom, part represents the laboratory work, and while the rest is in the form of e-learning (e-tutorials may be given via video-conferencing or with the help of specially designed e-material in a virtual electronic learning environment). Besides the aforementioned methods, students also use research metod and method of learning by doing.
Intended learning outcomes - knowledge and understanding
Knowledge and understanding:
Students:
learn to solve systems of linear inequasions using graphs,
learn the basics of linear programming,
learn to use linear programming to solve basic logistics problems,
learn to use LINGO and Microsoft Excel software to solve linear programmes,
learn to use concept of integer linear programming, and knows how to transform some of the graph theory problems to linear program problems,
learn to use DEA and AHP method.
Intended learning outcomes - transferable/key skills and other attributes
Transferable/Key Skills and other attributes:
The subject generally relates to all logistics subjects, as is in this one students learn quantitative modelling of typical logistical problems. Students learn how to apply theoretical knowledge to practical examples, especially at processes that they get to know at subject Fundamentals of logistics and supply chain.
Readings
Jensen, P. A., & Bard, J. F. (2003). Operations research: models and methods. John Wiley & Sons.
Kramberger, T., & Šinko, S. (2022). Optimizacijske metode v logistiki: osnovni problemi linearnega programiranja (1. izd.). Fakulteta za logistiko Univerze v Mariboru. https://fl.um.si/knjiznica/wp-content/uploads/2020/01/OPTIMIZACIJSKE-METODE-V-LOGISTIKI_PRVI-DEL.pdf
Kramberger, T., & Šinko, S. (2022). Optimizacijske metode v logistiki: upravljanje s pretoki in odločanje (1. izd.). Fakulteta za logistiko Univerze v Mariboru. https://fl.um.si/knjiznica/wp-content/uploads/2020/01/OPTIMIZACIJSKE-METODE-V-LOGISTIKI_DRUGI-DEL.pdf
Additional information on implementation and assessment Written examination 80%
E-lectures and e-courses 20%
