Facts about the course

ECTS Credits:
Responsible department:
Faculty of Logistics
Course Leader:
Arild Hoff
Lecture Semester:
Teaching language:
½ year

LOG904-126 Decision Modeling and Metaheuristics (Autumn 2019)

About the course

This is an applied course in which students will be exposed to a variety of decision modeling applications from business to supply chain management. It has two parts, the first one is based on mathematical models, and the second part on algorithmic coding. In the first part we apply Integer Linear Programming (ILP), Non-LP and MultiObjective methods in the Excel Solver to target logistic problems. In the second part we cover metaheuristic methodologies, by implementing GRASP and tabu search algorithms in Visual Basic for Excel.


Topics covered:

1. Modeling and Mathematical Programming,

2. Integer Models,

3. Global and Multi-Objective Optimization,

4. Metaheuristics: GRASP,

5. Metaheuristics: Tabu Search.

The course is connected to the following study programs

Recommended requirements

Basic concepts on Optimization and use of Excel>

The student's learning outcomes after completing the course

Become proficient in fact-based management. Create mathematical models, identify their structure, find and analyze results. Use the Excel spreadsheet to model and solve optimization problems. Code an algorithm in computer language to obtain heuristic solutions.

Forms of teaching and learning

A daily class from 9:15 to 12:00. These methodological classes are complemented with two sessions on applications: Tuesday and Thursday from 13:00 to 15:00.


Form of assessment: Home assessment without presentation

  • Proportion: 50%

  • Duration: -

  • Grouping: Individual

  • Grading scale: Letter (A - F)

  • Support material: All printed and written supporting material

Form of assessment: Written School assessment

  • Proportion: 50%

  • Duration: -

  • Grouping: Individual

  • Grading scale: Letter (A - F)

Support material:

Last updated from FS (Common Student System) Jan. 29, 2022 4:30:17 AM