GRA 6754 Operational Planning

GRA 6754 Operational Planning

Course code: 
GRA 6754
Department: 
Accounting and Operations Management
Credits: 
6
Course coordinator: 
Mehdi Sharifyazdi
Course name in Norwegian: 
Operational Planning
Product category: 
Master
Portfolio: 
MSc in Business - Logistics and Supply Chain Management
Semester: 
2025 Spring
Active status: 
Active
Level of study: 
Master
Teaching language: 
English
Course type: 
One semester
Introduction

This course delves into the intricate models, techniques, and strategies crucial for logistics and supply chain operational planning. Extending the knowledge base from GRA 6753 Operations Management, it enhances students' capabilities in modeling complex decision-making scenarios. The curriculum covers supply chain network design, facility location, and advanced scheduling models, emphasizing the application of decision trees, risk pooling, sensitivity analysis, simulation, and queuing models to manage uncertainty, risk, and variability. With a core focus on sustainability, this course prepares students to effectively manage resources and navigate the challenges of creating resilient and 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 how risk pooling strategies can mitigate risk
  • To examine the consequences of task sequencing on performance
Learning outcomes - Skills
  • To develop and solve linear programming (LP) and mixed-integer programming (MIP) models tailored to supply chain network design and planning challenges.
  • To perform sensitivity analysis to assess the impact of uncertain and variable input data on supply chain decisions.
  • To implement and evaluate risk pooling strategies under conditions of uncertainty.
  • To utilize simulation and queuing models to improve system performance and manage variability.
  • To optimize and evaluate the scheduling of tasks and activities.
General Competence
  • To craft and analyze optimization models for designing resilient supply chain networks, considering capacity, demand allocation, and the sustainable use of resources.
  • To analyze the sensitivity of the results of optimization models on uncertain or variable factors
  • To explore operational planning issues with a sustainability lens, focusing on economic, environmental, and societal impacts in alignment with the UN's Sustainable Development Goals 8, 9, and 12.
  • To navigate and mitigate risks in supply chain operations through comprehensive risk management strategies, such as risk pooling.
  • To assess and contrast various supply chain solutions across multiple timeframes, considering the time value of money and diverse possibilities amid uncertain circumstances
  • To appraise performance metrics in queuing systems
  • To determine efficient task sequences and schedules in operational planning
Course content
  • Supply Chain Network Design models
  • Handling of uncertainty and multiperiod planning.
  • Methods for conducting sensitivity analysis and simulation to model and manage operational variability and uncertainty.
  • Examination of risk pooling strategies, queuing theory, and the impacts of variability on process performance.
  • Techniques for effective scheduling and sequencing to optimize operational outcomes.
Teaching and learning activities

The course employs a practical, hands-on approach, primarily utilizing Microsoft Excel for modeling and analysis. Each topic begins with foundational theory, followed by exercises in Excel to apply concepts, fostering a learning-by-doing environment.

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

A computer with Microsoft Excel installed is required for all lectures.

Students bear the responsibility for acquiring any information provided during class sessions.

Qualifications

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.

Disclaimer

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

Required prerequisite knowledge
  • Completion of GRA 6753 Operations Management or an equivalent course.
  • A basic understanding of Microsoft Excel and Excel Solver, including formula manipulation and cell referencing. Students are encouraged to avail themselves of basic Excel training offered by BI or through free online resources such as Trump Excel.
Assessments
Assessments
Exam category: 
Submission
Form of assessment: 
Submission PDF
Exam/hand-in semester: 
First Semester
Weight: 
100
Grouping: 
Individual
Duration: 
5 Hour(s)
Comment: 
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: 
ECTS
Resit: 
Examination when next scheduled course
Type of Assessment: 
Ordinary examination
Total weight: 
100
Student workload
ActivityDurationComment
Teaching
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
Examination
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: 
161

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.