The University of Southampton

MANG6046 Optimisation and Decision Modelling

Module Overview

This module will provide you with a sound foundation in the application of the many tools and techniques of management science. You are expected to learn the tools and the applications of modelling, optimization, computing and programming in solving practical problems drawn from many functional areas (operations, finance, marketing, and human resources, etc.) in different organizations (industry, finance, public sector, etc.).

Aims and Objectives

Module Aims

• To familiarize you with the tools of linear programming and its extensions. • To teach you how to identify, formulate and solve problems which are amenable to optimisation formulation. • To allow you to use a standard solution package and interpret its output.

Learning Outcomes

Knowledge and Understanding

Having successfully completed this module, you will be able to demonstrate knowledge and understanding of:

  • model a wide range of business problems using optimisation techniques;
  • solve linear programming problems using different techniques;
  • obtain sensitive analysis reports, and understand the concept of duality;
  • recognise and be able to formulate and solve problems that require integer programming and goal programming;
  • use a standard linear programming package.
Transferable and Generic Skills

Having successfully completed this module you will be able to:

  • problem structuring and solving;
  • decision making;
  • teamwork;
  • computer skills
Subject Specific Intellectual and Research Skills

Having successfully completed this module you will be able to:

  • apply the principles and techniques to solve practical business problems;
  • critically analyse and interpret the solutions of decision-making.


• Model building for business problems. Linear programming model formulation and graphical solution. Analysis of special linear programming solutions • Linear programming applications and their computer solution • The Simplex method for solving linear programming • Duality and sensitivity analysis in linear programming, including graphical sensitivity analysis, simplex-based sensitivity analysis, and computer sensitivity analysis • Goal programming and integer programming • Shortest path problems (also briefly covering dynamic programming framework and principles). • Decision analysis and decision tree

Learning and Teaching

Teaching and learning methods

Made up of 24 lectures. No seminars or tutorials. Students are allowed to select their own group members, normally 4 students in a group. Since the assignment is about mathematical modelling, students are expected to arrange all meeting themselves, including discussing problems, building up models, solving the models using software arrange, and writing reports. There will be a very brief introduction about group work, which normally occurs during lectures.

Independent Study126
Total study time150

Resources & Reading list

BW Taylor III (2012). Introduction to Management Science. 

B Render, RM Stair Jr. and N Balakrishnan (2012). Managerial Decision Modelling with Spreadsheets. 

DR Anderson, DJ Sweeney, TA Williams AND M Wisniewski (2010). Introduction to Management Science: Quantitative Approach to Decision Making (Int'l Ed). 

FS Hillier and MS Hillier (2013). Introduction to Management Science: a Modelling and Case Study Approach with Spreadsheets. 



Questions and answers


MethodPercentage contribution
Examination  (2 hours) 60%
Group project  (2000 words) 40%


MethodPercentage contribution
Examination  (2 hours) 100%


MethodPercentage contribution
Examination  (2 hours) 100%
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