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Constraint Programming (COMP90046)

Graduate courseworkPoints: 12.5Not available in 2018

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Overview

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AIMS

The aims for this subject is for students to develop an understanding of approaches to solving combinatorial optimization problems with computers, and to be able to demonstrate proficiency in modelling and solving programs using a high-level modelling language, and understanding of different solving technologies. The modelling language used is MiniZinc.

INDICATIVE CONTENT

Topics covered will include:

  • Modelling with Constraints
  • Global constraints
  • Multiple Modelling
  • Model Debugging
  • Scheduling and Packing
  • Finite domain constraint solving
  • Mixed Integer Programming

Intended learning outcomes

INTENDED LEARNING OUTCOMES (ILO)


On completion of this subject the student is expected to:



  • Model a complex constraint problem using a high level modelling language
  • Define and explore different search strategies for solving a problem
  • Explain how modelling interacts with solving algorithms, and formulate models to take advantage of this using state of the art optimisation tools
  • Explain different optimization technologies, and their strengths and weaknesses

Generic skills

On completion of this subject students should be able to have the following skills:

  • Undertake problem identification, formulation, and solution
  • Utilise a systems approach to complex problems and to design and for operational performance
  • Manage information and documentation in solution creation
  • Demonstrate improved capacity for creativity and innovation.

Last updated: 3 November 2022