SIMULATION AND OPTIMISATION - 2022/3

Module code: MAN2187

Module Overview

Prescriptive analytics area such as optimisations and simulations will be introduced for decision making in a business environment. Several typical business scenarios will be analysed using Discrete Event Simulations. Optimisations will be used in a business context.

Module provider

Surrey Business School

Module Leader

GARN Wolfgang (SBS)

Number of Credits: 15

ECTS Credits: 7.5

Framework: FHEQ Level 5

JACs code:

Module cap (Maximum number of students): N/A

Overall student workload

Independent Learning Hours: 117

Lecture Hours: 22

Seminar Hours: 11

Module Availability

Semester 2

Prerequisites / Co-requisites

N/A

Module content

The module content will focus on simulation and optimisation. Please find below an indicative set of topics.

· Optimisations using Linear and Integer Programming

· Network Flow Optimisations

· Optimal Transportation Models

· Queueing System

· Inventory Management

· Discrete Event Simulation (DES)

· DES software, Applied DES

· System Dynamics, Agent Based Simulation

Assessment pattern

Assessment type Unit of assessment Weighting
Online Scheduled Summative Class Test Weekly online tests 20
Project (Group/Individual/Dissertation) Simulation group coursework 40
Examination Simulation and optimisation exam 40

Alternative Assessment

An alternative to the group project is a defined individual project using a business problem with a specific description (750 words for the individual).

Assessment Strategy

The assessment strategy is designed to provide students with the opportunity to demonstrate that they:

· appreciate methods that underpin Operational Research;

· use simulations to gain business insights;

· demonstrate abilities of finding optimal solutions for business opportunities.

 

The summative assessment for this module consists of

· Simulation and optimisation exam (40%)
2-hour closed book examination taken at the end of the semester.

· Simulation group coursework (40%).
2000 words group coursework to assess to be submitted at the end of the semester.

· Weekly Online Tests (20%)
10 weekly formally assessed quizzes after each lecture (each quiz carries 2 marks total 20).

 

Formative assessment and feedback
Students will be given the opportunity to receive formative assessment and feedback relevant to the assignments. Formative assessment relevant to the closed book exam may be provided on SurreyLearn discussion forums.

 

Feedback
The exam and assignments will contain information of what topic areas the student knows well and not so well, and how the student can further improve her/his performance.

The assignment feedback will be automated and provided via SurreyLearn on submission. The student is encouraged to seek further feedback during the lab sessions or during feedback and consultation hours.

Module aims

  • Introduce students to key theories in modelling and simulation;
  • Allow students to gain insights to the field of Prescriptive Analytics with a focus on optimisations;
  • To enable students to use simulations and optimisations for decision making.

Learning outcomes

Attributes Developed
001 To gain insights in how to formulate solve optimisation challenges CKP
002 To critically evaluate and select relevant prescriptive analytical methods to improve business productivity CKPT
003 To gain insights in how to create simulation models and explain their results. CKP
004 To effectively communicate and provide results to stakeholders and decision makers for implementation PT

Attributes Developed

C - Cognitive/analytical

K - Subject knowledge

T - Transferable skills

P - Professional/Practical skills

Methods of Teaching / Learning

The learning and teaching strategy is designed to encourage critical understanding of the role played by analytics for business decision making. Learning will be directed, supported and reinforced through a combination of lectures, computer laboratory sessions, and online discussion groups, plus directed and self-directed study. The course may include research-led elements and offers a mix of theoretical insights and case study material that will be delivered both online and offline where appropriate.

Indicated Lecture Hours (which may also include seminars, tutorials, workshops and other contact time) are approximate and may include in-class tests where one or more of these are an assessment on the module. In-class tests are scheduled/organised separately to taught content and will be published on to student personal timetables, where they apply to taken modules, as soon as they are finalised by central administration. This will usually be after the initial publication of the teaching timetable for the relevant semester.

Reading list

https://readinglists.surrey.ac.uk
Upon accessing the reading list, please search for the module using the module code: MAN2187

Other information

N/A

Please note that the information detailed within this record is accurate at the time of publishing and may be subject to change. This record contains information for the most up to date version of the programme / module for the 2022/3 academic year.