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 - Supply Chain and Operations Management
Semester: 
2022 Spring
Active status: 
Active
Level of study: 
Master
Teaching language: 
English
Course type: 
One semester
Introduction

In this course, students will learn key models, methods and strategies for logistics and supply chain operational planning and how to apply them. This course is built upon the course operations management where students have learned about basics of optimization in supply chain and logistics planning, demand forecasting, inventory planning, production planning, pricing and capacity planning. Operational planning extends students’ modelling skills and discusses models and strategies for supply chain network design, facility location, scheduling and project management. In addition, they will learn to use concepts, models and methods such as, decision trees, risk pooling, sensitivity analysis, simulation and queuing models to cope with uncertainty and variability in supply chain and operational planning.

Learning outcomes - Knowledge
  • To identify and interpret the basic trade-offs in supply network design and supply chain planning.
  • To describe how the use of LP and MIP models can reduce sub-optimization in such systems.
  • To theorize how service time variability can affect a process.
  • To explain how risk pooling strategies can help to reduce risk.
  • To analyze the effects of sequencing of tasks on performance
Learning outcomes - Skills
  • To formulate, use and solve LP and MIP based models for supply network design and supply chain planning using Excel's standard solver.
  • To analyse 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 scheduling of tasks and activities.
General Competence
  • To make customized optimization models for supply chain network design and capacity/demand allocation
  • To compare different supply chain solutions through multiple periods taking into account the time value of money and different possibilities in uncertain conditions
  • To find suitable risk pooling solutions to cope with uncertainty and risk in supply chains
  • To evaluate performance measures in queuing systems
  • To find optimal or good enough sequence and time table of tasks in operational planning
  • To model and analyse projects by finding critical paths, calculating slack times and other network analyses
Course content
  • Supply Chain Network Design
  • Dealing with uncertainty and multi-periodicity in Supply Chain Planning
  • Sencitivity analysis and simulation
  • Variability and its Impact on Process Performance
  • Waiting lines
  • Risk Pooling Strategies
  • Scheduling and sequencing
  • Project management
Teaching and learning activities

The course is mainly delivered in a learning-by-doing manner. 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. 

Please note that while attendance is not compulsory in all courses, it is the student’s own responsibility to obtain any information provided in class.

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 spesific prerequisites and will assume that students have followed normal study progression. For double degree and exchange students, please note that equivalent courses are accepted.

Covid-19 

Due to the Covid-19 pandemic, there may be deviations in teaching and learning activities as well as exams, compared with what is described in this course description.

Teaching 

Information about what is taught on campus and other digital forms will be presented with the lecture plan before the start of the course each semester.

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: https://excelexposure.com/lesson-guide/.)
Exam categoryWeightInvigilationDurationSupport materialsGroupingComment exam
Exam category:
Submission
Form of assessment:
Written submission
Exam code:
GRA67541
Grading scale:
ECTS
Grading rules:
Internal and external examiner
Resit:
Examination when next scheduled course
100Yes5 Hour(s)
  • All printed and handwritten support materials
  • BI-approved exam calculator
  • Simple calculator
Individual Written examination under supervision. The exam is digital, majorly carried out on Excel.
Exams:
Exam category:Submission
Form of assessment:Written submission
Weight:100
Invigilation:Yes
Grouping (size):Individual
Support materials:
  • All printed and handwritten support materials
  • BI-approved exam calculator
  • Simple calculator
Duration:5 Hour(s)
Comment:Written examination under supervision. The exam is digital, majorly carried out on Excel.
Exam code: GRA67541
Grading scale:ECTS
Resit:Examination when next scheduled course
Type of Assessment: 
Ordinary examination
Total weight: 
100
Sum workload: 
0

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.