Operational Research module (MA22005)

How do businesses make the best use of limited resources? How do delivery networks reduce costs while keeping things running on time? Operational research is the maths of decision-making, and this module introduces you to the tools that make it possible.

You’ll learn how to build and solve mathematical models that describe real-world problems in logistics, planning, and resource allocation. You’ll start with linear programming, using the graphical method and the Simplex algorithm. You'll then be able to find the best solutions within constraints.

You'll also study duality and sensitivity analysis. This will enable you to understand how solutions change when conditions do.

Later in the module, you’ll tackle transportation and assignment problems. These are used in everything from supply chains to staff scheduling. The techniques you'll use include the primal-dual method and the Hungarian algorithm. These methods aren’t just theoretical, they’re applied every day in industries around the world.

Whether you’re interested in business, engineering, or applied maths, this module gives you practical skills in optimisation, critical thinking, and problem-solving.

What you will learn

In this module, you will:

• translate real-world problems into linear programming models
• solve linear programmes using graphical and Simplex methods
• study duality and perform basic sensitivity analysis
• apply branch and bound techniques to integer linear problems
• solve transportation and assignment problems using standard algorithms

By the end of this module, you will be able to:

• formulate and solve optimisation problems using mathematical techniques
• use linear programming methods confidently, including duality concepts
• solve transport and assignment problems efficiently
• select appropriate algorithms and interpret results in context

Assignments / assessment

• Coursework (40%)
• Final written exam, two hours (60%)

Teaching methods / timetable

• Lectures
  • Learn core techniques through worked examples and discussions
• Tutorials
  • Practise solving real-world problems with personalised support in a small group setting