TLOG2009 - Optimization of Logistics Systems


Examination arrangement

Examination arrangement: School exam
Grade: Letter grades

Evaluation Weighting Duration Grade deviation Examination aids
School exam 100/100 4 hours E

Course content

The subject's position and function in the study:

The subject is compulsory in the 1st year, 2nd semester of the study program INGLOG (Program subject basis subject 2), and should concretely contribute to providing a basic understanding of optimization, and skills in modeling and optimizing key issues in logistics, e.g. production planning, transport planning, capacity and resource planning, systems with stochastic uncertainty, and systems with queuing.

Academic content

  • Introduction to linear programming and optimization;
  • Linear models with a focus on issues from logistics;
  • Network modeling; Integer modeling;
  • Non-linear models with a focus on issues from logistics;
  • Forecasting models
  • Queue models
  • Simulation models with statistical uncertainty

Learning outcome

Knowledge: The course must convey the following knowledge to the candidate

  • General knowledge of linear programming (LP) and optimization
  • Specific knowledge of the use of LP and optimization for key issues within logistics, e.g. production planning, capacity and resource planning, transport and distribution networks
  • Specific knowledge of integer calculations is essential
  • Specific knowledge of solving/optimizing non-linear systems
  • Specific knowledge of forecasting and demand management
  • Specific knowledge of creating simulation models for systems exposed to statistical uncertainty
  • General knowledge of queuing theory and how to solve simple queuing systems

Skills: The candidate must be able to:

  • Build models for various logistics-related issues such as production planning, capacity and resource planning, transport and distribution planning in Excel and find an optimized solution.
  • Build models and find optimized solutions with integer calculations
  • Build models and find optimized solutions for non-linear issues in logistics and value chain management, e.g. order quantity or facility location
  • Carry out forecasting for demand and sales data with seasonal variations
  • Build simulation models with statistical uncertainty for various logistics-related issues
  • Analyze and save for simple queuing systems

General skills: The candidate must be able to

  • Understand the role of optimization in an overall economic and logistic analysis perspective
  • Be able to apply optimization in logistics and value chain management in general and in particular with regard to the new developments in the digitization era.
  • Understand the ethical values ​​of Scientific Management in general, and optimization discipline in particular.
  • Understand the role of optimization and planning discipline and its contribution to a more sustainable future in logistics operations in general.
  • Understand the strong relationship between Management Science and impact on innovation performance.
  • Gain a broad knowledge of digital models for real systems within logistics and how they can be of great value for the optimization of resource use and efficiency.

Learning methods and activities

PC-based lectures and exercises. Lectures will be through the usage of PC and interactive with the class. Individual exercises with submission.

Compulsory assignments

  • Exercise

Further on evaluation

Written digital school exam.

Compulsory work: 6 exercises. 5 must be passed in order to sit for the exam.

Compulsory activity from previous semesters can be approved by the department.

The continuation exam can be changed to an oral exam.

Specific conditions

Admission to a programme of study is required:
Logistics engineering (FTHINGLOG)

Course materials

1) Textbook: Practical Management Science, Winston & Albright, 6th edition, Cengage Learning, 2018.

2) Lecture Notes, Handouts

More on the course



Version: 1
Credits:  7.5 SP
Study level: Intermediate course, level II


Term no.: 1
Teaching semester:  SPRING 2024

Language of instruction: Norwegian

Location: Trondheim

Subject area(s)
  • Engineering
Contact information
Course coordinator:

Department with academic responsibility
Department of Industrial Economics and Technology Management


Examination arrangement: School exam

Term Status code Evaluation Weighting Examination aids Date Time Examination system Room *
Spring ORD School exam 100/100 E INSPERA
Room Building Number of candidates
Summer UTS School exam 100/100 E INSPERA
Room Building Number of candidates
  • * The location (room) for a written examination is published 3 days before examination date. If more than one room is listed, you will find your room at Studentweb.

For more information regarding registration for examination and examination procedures, see "Innsida - Exams"

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