GRA 6754 Operational Planning

GRA 6754 Operational Planning

Course code: 
GRA 6754
Accounting and Operations Management
Course coordinator: 
Mehdi Sharifyazdi
Course name in Norwegian: 
Operational Planning
Product category: 
MSc in Business - Logistics and Supply Chain Management
2024 Spring
Active status: 
Level of study: 
Teaching language: 
Course type: 
One semester

In this course, students will explore essential models, techniques, and approaches for logistics and supply chain operational planning, as well as their application. Building upon the foundation established in the course GRA 6753 Operations Management, which covered topics such as optimization in supply chain and logistics planning, demand forecasting, inventory planning, production planning, pricing, and capacity planning, this course further expands students' modeling abilities. It delves into supply chain network design, facility location, and scheduling models and strategies.

Moreover, students will acquire proficiency in utilizing concepts, models, and methods like decision trees, risk pooling, sensitivity analysis, simulation, and queuing models to address uncertainty, risk, and variability in supply chain and operational planning. In the current business environment, where sustainability is a core principle, the course equips students with the skills to efficiently plan and allocate limited resources, which is vital for achieving sustainability objectives. Additionally, the course imparts methodologies for managing various forms of uncertainty and risk, fostering resilience essential for sustainable supply chains.

Learning outcomes - Knowledge
  • To pinpoint and interpret fundamental trade-offs in supply network design and supply chain planning
  • To comprehend the role of supply chain network design in accomplishing sustainability objectives, such as minimizing carbon footprint
  • To recognize and reflect on the impact of uncertainty and variability on supply chain network design decisions
  • To grasp the translation of sustainable resilience into uncertainty modeling within supply chain planning
  • To theorize the influence of service time variability on a given process
  • To explain the ways in which risk pooling strategies can mitigate risk
  • To examine the consequences of task sequencing on performance
Learning outcomes - Skills
  • To formulate, use and solve LP and MIP models for supply chain network design and supply chain planning
  • To examine the sensitivity of supply chain network decisions to uncertainty and variability of input data
  • To analyze and compare different alternatives in supply network design and supply chain planning, taking into account uncertainty and temporal value of money
  • To measure and improve the performance of queuing systems with uncertain arrival and service processes
  • To apply and estimate the effects of risk pooling strategies.
  • To optimize and evaluate the scheduling of tasks and activities.
General Competence
  • To create tailored optimization models for supply chain network design, along with capacity and demand allocation
  • To conduct sensitivity analysis experiments on the results of optimization models
  • To assess and contrast various supply chain solutions across multiple timeframes, considering the time value of money and diverse possibilities amid uncertain circumstances
  • To identify appropriate risk pooling strategies for managing uncertainty and risk in supply chains
  • To appraise performance metrics in queuing systems
  • To determine optimal or satisfactory task sequences and schedules in operational planning
  • To delve into subjects relevant to business, economy, production, transportation, environment, and society, in accordance with the UN's Sustainable Development Goals 8, 9, and 12
Course content
  • Supply Chain Network Design
  • Dealing with uncertainty and multi-periodicity in Supply Chain Planning
  • Sensitivity analysis
  • Simulation
  • Variability and its Impact on Process Performance
  • Waiting lines
  • Risk Pooling Strategies
  • Scheduling and sequencing
Teaching and learning activities

For each topic of the course, first, a short theoretical and practical background is given. Then, it is mainly delivered in a learning-by-doing manner in Microsoft Excel environment. Students will make different models in Excel during the class and do exercises on extensions of those models outside of the class.

Software tools
Software defined under the section "Teaching and learning activities".
Additional information

It is necessary that the students have a computer with them (with Excel installed on it) during the lectures. 

It is the student’s own responsibility to obtain any information provided in class.


All courses in the Masters programme will assume that students have fulfilled the admission requirements for the programme. In addition, courses in second, third and/or fourth semester can have specific prerequisites and will assume that students have followed normal study progression. For double degree and exchange students, please note that equivalent courses are accepted.


Deviations in teaching and exams may occur if external conditions or unforeseen events call for this.

Required prerequisite knowledge
  • GRA 6753 Operations Management or equivalent
  • Basic knowledge of Microsoft Excel and Excel Solver, especially, how to enter and copy formulas and use relative and absolute addresses. (Basic Excel courses are offered at BI, but the students can also find free online tutorials including videos and exercises here:
Exam category: 
Form of assessment: 
Written submission
5 Hour(s)
The assessment is in the form of an open-book home exam since it is completely carried out on Excel.
Exam code: 
GRA 67541
Grading scale: 
Examination when next scheduled course
Type of Assessment: 
Ordinary examination
Total weight: 
Student workload
24 Hour(s)
Participation in the class
Student's own work with learning resources
12 Hour(s)
Asynchronous lectures
Student's own work with learning resources
48 Hour(s)
Reading textbook and lecture notes and watching uploaded videos
Individual problem solving
60 Hour(s)
Solving/completing given exercises at home
5 Hour(s)
Prepare for teaching
12 Hour(s)
Go through lecture notes and selected textbook sections before the synchronous lecture in the class
Sum workload: 

A course of 1 ECTS credit corresponds to a workload of 26-30 hours. Therefore a course of 6 ECTS credits corresponds to a workload of at least 160 hours.