Foundations of OR: Optimisation and (Meta-) Heuristics

A practical introduction to the most used methodologies in OR, linear programming and optimisation.

Description

  • Understand the potential and limitations of optimisation methodologies 
  • Become aware of the scope of applications of optimisation 
  • Be able to apply linear programming in your own work 
  • Be able to solve a linear program using Excel Solver or another program 
  • Be able to interpret a solution to a linear program 
  • Become aware of alternative optimisation methodologies and understand when to use which approach 
  • Become aware of heuristic approaches to optimisation and their advantages and limitations

Learning objectives

  • Learn about the potential and limitations of optimisation methodologies 
  • Understand the scope of applications of optimisation 
  • Apply linear programming by solving a problem using Excel Solver 
  • Interpret the solution to a linear program 
  • Build your knowledge of alternative optimisation methodologies and understand when to apply different approaches 
  • Learn about heuristic approaches to optimisation and their advantages and limitations. 

Topics

  • The application of linear programming in different sectors 
  • Decision variables, objective function, and constraints 
  • Graphical illustrations of linear programs 
  • Using Excel Solver to solve and interpret linear programs 
  • Sensitivity analysis 
  • Common types of linear programs, including transportation 
  • Other types of optimisation problems 
  • Introduction to metaheursitic approaches as alternatives to exact methods 

Audience

The course is designed for those with limited or no prior experience in optimisation. The hands-on experience with optimisation provided during the course will enable delegates to recognise potential of optimisation and start applying it in their own work. 

 

Course format

  • PowerPoint presentation to introduce the topics including illustrative examples from different sectors 
  • Case studies based on ‘real world’ problems 
  • Practical sessions using Microsoft Excel with the Solver tool pack 
  • Group discussion/work to explore the topics in more detail 
  • Bring questions from your own work to embed your learning 
  • Supporting resource pack available to use following the course 

Related courses

  • Foundations of OR: Data Envelopment Analysis 
  • Foundations of OR: Statistical Methods in OR: Multivariate Statistics 
  • Foundations of OR: Follow on to Forecasting: ARIMA modelling for forecasting 

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