GRA 4138 Business Simulation Analysis

GRA 4138 Business Simulation Analysis

Course code: 
GRA 4138
Department: 
Accounting, Auditing and Business Analytics
Credits: 
6
Course coordinator: 
Erna Engebrethsen
Mehdi Sharifyazdi
Product category: 
Master
Portfolio: 
MSc in Business Analytics
Semester: 
2020 Spring
Active status: 
Active
Teaching language: 
English
Course type: 
One semester
Introduction

The course objective is to familiarize the students with computer-based simulation methodologies and tools used in business settings characterized by uncertainties. The course will utilise both lectures and exercises.

Learning outcomes - Knowledge
  • Knowledge of discrete-event simulation methodology and relevant background theories
  • Knowledge of Monte-Carlo simulation methodology and relevant background theories
Learning outcomes - Skills
  • Modelling and analysis of various systems using discrete-event simulation and Monte-Carlo techniques and tools
  • Effective interpretation and demonstration of model outputs
  • Sensitivity analysis
General Competence
  • To identify real-world problems to which simulation methods are useful and relevant
  • To understand and appreciate the way uncertain and variable factors affect performance of various systems and how simulation helps to model, design, improve and analyse such systems
Course content

The course participants will learn how to model various systems, and study the effect on changes and uncertainties on the system in order to identify bottlenecks and improvements areas. Examples of simulations application areas include inventory and transportation systems, production environment, investments evaluation, queuing systems etc.  The course will focus on modelling and analyzing systems using Discrete Event Simulations and Random event generators (Monte-Carlo simulations). The students will exercise on using simulation tools and on interpreting and presenting the results.

Teaching and learning activities

The course consists of lectures, tasks, presentations and discussions. 

The following software tools are to be used during the course: 

  • Anylogic
  • Excel and relevant add-ins

 

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

    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.

    This is a course with continuous assessment (several exam components). Each exam component is graded by using points on a scale from 0-100. The components will be weighted together according to the information in the course description in order to calculate the final letter grade course. Students who fail to participate in one/some/all exam elements will get a lower grade or may fail the course. You will find detailed information about the point system and the cut off points with reference to the letter grades when the course starts.

    At resit, all exam components must, as a main rule, be retaken during next scheduled course.

    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.

    Required prerequisite knowledge
    • Basics of probability theory
    • Basics of Microsoft Excel
    Exam categoryWeightInvigilationDurationGroupingComment exam
    Exam category:
    Submission
    Form of assessment:
    Written submission
    Exam code:
    GRA 41381
    Grading scale:
    Point scale
    Grading rules:
    Internal examiner
    Resit:
    All components must, as a main rule, be retaken during next scheduled course
    20No1 Month(s)Group/Individual (1 - 3) Course paper - Monte-Carlo simulation
    Exam category:
    Activity
    Form of assessment:
    Presentation
    Exam code:
    GRA 41381
    Grading scale:
    Point scale
    Grading rules:
    Internal examiner
    Resit:
    All components must, as a main rule, be retaken during next scheduled course
    10No15 Minute(s)Group/Individual (1 - 3) Presentation of papers
    Exam category:
    Submission
    Form of assessment:
    Written submission
    Exam code:
    GRA 41381
    Grading scale:
    Point scale
    Grading rules:
    Internal and external examiner
    Resit:
    All components must, as a main rule, be retaken during next scheduled course
    70No1 Semester(s)Group/Individual (1 - 3) Term paper (Project) - Discrete-event simulation
    Exams:
    Exam category:Submission
    Form of assessment:Written submission
    Weight:20
    Invigilation:No
    Grouping (size):Group/Individual (1-3)
    Duration:1 Month(s)
    Comment: Course paper - Monte-Carlo simulation
    Exam code: GRA 41381
    Grading scale:Point scale
    Resit:All components must, as a main rule, be retaken during next scheduled course
    Exam category:Activity
    Form of assessment:Presentation
    Weight:10
    Invigilation:No
    Grouping (size):Group/Individual (1-3)
    Duration:15 Minute(s)
    Comment: Presentation of papers
    Exam code: GRA 41381
    Grading scale:Point scale
    Resit:All components must, as a main rule, be retaken during next scheduled course
    Exam category:Submission
    Form of assessment:Written submission
    Weight:70
    Invigilation:No
    Grouping (size):Group/Individual (1-3)
    Duration:1 Semester(s)
    Comment: Term paper (Project) - Discrete-event simulation
    Exam code: GRA 41381
    Grading scale:Point scale
    Resit:All components must, as a main rule, be retaken during next scheduled course
    Type of Assessment: 
    Continuous assessment
    Grading scale: 
    ECTS
    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.