Catalogue of Modules, University of Nottingham

G54ORM Operations Research and Modelling
(Last Updated:03 May 2017)

Year  11/12

Total Credits: 10

Level: Level 4

Target Students:  MSc and Part III undergraduate students only in the School of Computer Science and the School of Mathematics. Also available to students from other Schools with the agreement of the module convenor.  Available to JYA/Erasmus students.

Taught Semesters:

SemesterAssessment
Autumn Assessed by end of Autumn Semester 

Prerequisites: Knowledge of algorithm basics, data structures and some computer programming. Knowledge of the basics of: linear algebra and calculus is desirable.

Corequisites:  None.

Summary of Content:  

This module is part of the Modelling and Optimisation theme in the School of Computer Science.

The module provides an entry point to operations research for students in MSc courses and is also a follow-up for students who took G53ORO already. The module covers a range of operations research techniques (emphasis here is on learning modelling techniques) in order to tackle a range of real-world problems. Operations research (OR) is a discipline that uses modelling techniques, analytics and computational methods to solve complex problems in industry and business with the aim of helping to make better decisions. By using operation research techniques to analyse complex situations, decision-makers are able to make more effective decisions and build more productive systems. Topics covered in this module include: Introduction to OR, Linear Programming, Modelling and Optimisation Software, Post-optimality Analysis, Integer Programming, Modelling Techniques, Combinatorial Optimisation, Solving Large IP Models and Dynamic Programming. Students learn to interpret and create formal models of optimisation problems and then to develop computer-based solutions by means of spreadsheets and/or programming style systems. Techniques are explained using numerical examples and their application is illustrated using a number of case studies and software tools (e.g. optimisation solvers such as Excel, Lingo, Gams and others).

Module Web Links:
   
  • Module Web Page
  • Method and Frequency of Class:

    ActivityNumber Of WeeksNumber of sessionsDuration of a session
    Lecture 11 weeks1 per week2 hours
    Practical 11 weeks1 per week1 hour

    Activities may take place every teaching week of the Semester or only in specified weeks. It is usually specified above if an activity only takes place in some weeks of a Semester

    Method of Assessment: 

    Assessment TypeWeightRequirements
    Exam 1 50 1.5hr Written examination (problem modelling/solving) 
    Coursework 1 30 Apply modelling and optimisation solvers to solve a real-world scenario and write a report about the assignment 
    Inclass Exam 1 (Written) 20 Weekly online quiz based on workshops that might include writing models and using optimisation solvers 

    Convenor: 
    Dr D Landa Silva

    Education Aims:  
    To develop an understanding of operations research techniques with emphasis on theory, applications and computations. To develop the skills for modelling a range of decision and optimisation problems in business and industry using mathematical models. To implement operation research techniques to solve specific optimisation problems using optimisation software tools.

    Learning Outcomes:  
    Knowledge and Understanding:
    The strengths and weaknesses of computer tools, applications and other resources.
    Applied mathematics and formal methods in the computer science context.

    Intellectual Skills:
    Apply and deploy mathematical ability, practices and tools.
    Understand complex ideas and relate them to specific problems or questions.

    Professional Practical Skills:
    Program in various paradigms.
    Evaluate available tools, applications, algorithms and data structures, and select those that are fit for purpose within a given domain.

    Transferable Skills:
    Solve problems.
    Utilise mathematics.

    Offering School:  Computer Science


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