Facts about the course

Study points:
2.5
Responsible department:
Faculty of Logistics
Course Leader:
Berit Irene Helgheim
Lecture Semester:
Autumn
Teaching language:
English
Duration:
½ year

LOG904-152 Oil, gas and renewable energy logistics problems with uncertainty (Autumn 2018)

About the course

The course will present the basic concepts of optimization under uncertainty (Stochastic Optimization, Robust optimization and Risk models) on simple logistics planning problems and their application to actual problems in the oil, gas and renewable energy logistics systems. Examples of these models are the oil & gas strategic planning problem, the biodiesel supply chain optimization, hydrogen fuel supply chain or the refinery production planning problem.

Topics covered: Stochastic Optimization; Robust Optimization; Mathematical Programming Modeling; Oil & Gas Supply Chain; Renewable Energy Logistics; Network Design

The course is connected to the following study programs

Recommended requirements

LOG716 ¿ Mathematical Modelling in Logistics

The student's learning outcomes after completing the course

Students will be able to choose the most appropriate stochastic optimization approach to solve logistics planning problems under uncertainty and also be able to develop simple stochastic models and to solve them using optimization software.

Forms of teaching and learning

Four mandatory modelling assignments and presentation of one paper on selected topics

Coursework requirements - conditions for taking the exam

  • Mandatory coursework: Assignment(s)
  • Courseworks given:
  • Courseworks required:
  • Presence: Not required
  • Comment: Implementation of given modeling exercises in AMPL

Examination

  • Form of assessment: Home assessment
  • Proportion: 50%
  • Duration: -
  • Grouping: Group
  • Grading scale: Letter (A - F)
  • Support material: All printed and written supporting material
  • Form of assessment: Home assessment
  • Proportion: 50%
  • Duration: -
  • Grouping: Group
  • Grading scale: Letter (A - F)
  • Support material: All printed and written supporting material

Syllabus

A set of selected articles.

Last updated from FS (Common Student System) Apr. 19, 2019 6:30:07 PM