Current 2016/17 Module Catalogue

Module Details

Module Code:
Module Provider:
Surrey Business School
Number of Credits:
Module Title:
Module Co-ordinator:
ECTS Credits

Module Availability

Semester 2

Assessment Pattern

Assessment TypeUnit of AssessmentWeighting %
Examination2 Hour Examination50
CourseworkCoursework (Students Demonstrate The Ability To Solve Problems During The Course Of The Semester)50

Module Overview

Management Science is used to solve supply chain (SC) aspects analytically. Techniques examine the Supply Chain’s underlying transportation network which connects suppliers via transhipment nodes to its demand locations. Best locations for warehouses (or transhipment nodes) are determined using quantitative methods. Decision Science is used for in rational decision making under uncertainty. For instance optimal inventory levels are determined for warehouses and manufacturing. All kinds of business activities are optimised to give businesses a competitive advantage by maximising profit and minimising costs.



Module Aims

To solve Supply Chain problems analytically.

Learning Outcomes

On successful completion of this module, at threshold level, students will be able to:

  • analyse the efficiency and productivity of business firms;
  • evaluate and define “challenges” in a concise, precise and logical   manner;
  • apply a selected number of classical and state-of-the art Operational Research methods and tools to solve supply chain problems analytically;
  • create solution models and algorithms that offer competitive advantage to the businesses;
  • provide results to the management for decision making and implementation.


Module Content

The module content will focus on a selected set of critical areas in Management. As an indication of the kind of issues that will be covered, please find below an indicative set of topics.

  • Decision Analysis (e.g. Utility theory)
  • Linear Programming (e.g. transportation optimisations)
  • Network Analysis  (e.g. Shortest Route, minimal spanning tree)
  • Inventory Systems (e.g. Economic Order Quantity model)
  • Simulations and Waiting Line Models (e.g. Multiple Server Waiting Line)


Methods of Teaching/Learning

The teaching and learning strategy is designed to: cultivate an understanding of the main issues and challenges; provide a coherent conceptual framework; develop a critical awareness of the various approaches of operational research in business firms.

 The teaching and learning methods include: a lecture every week as well as several student exercises. Web-based learning support and electronic resources will be provided.



In order to achieve the threshold standard for the award of credits for this module, the student must meet the following criteria related to the learning outcomes:

  • apply the theories, conceptual frameworks and methodologies that underpin operational research;
  • prove the ability to synthesise Management Science concepts within an analytical context;
  • demonstrate evidence of background reading and research of the academic and practitioner literature relevant to Management Science.


Formative assessment will be provided throughout the course, i.e. students demonstrate ability to solve problems during the course of the semester. They will be given four business problems per week (i.e. 40 for the whole semester) as homework. Each student has to present two solutions during the semester. Presentations are scheduled in week 3, 5, 7, 9 and 11. For instance in week w3 student s must have prepared 6 solutions out of 8. Student s will be asked to present the solution (using prepared notes) and obtains m1.  Student s will not be asked a second time in the same week. However student s might have to present another solution in week w9. In case student s cannot attend one of the presentations, then six exercises should be submitted to the module convenor and the student might be invited to present one of them.

Module Hours

Lecture Hours:22

Tutorial Hours:10

Lab Hours:12

Reading List


Last Updated

30 April 2014 by FARZULLAYEVA N Mrs (FBEL Reg)