Total Credits: 20
Level: Level 4
Target Students: MSc and undergraduate students (part II and part III) 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.This module is part of the AI, Modelling and Optimisation theme in the School of Computer Science. Available to JYA/Erasmus students.
|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.
Summary of Content: The module provides an entry point to operations research with emphasis in techniques for computational optimisation. Operations research (OR) is a discipline that uses modelling techniques, analytics and computational methods to solve complex optimisation problems in industry and business. You will learn to interpret and create formal models of optimisation problems and to develop computer-based solutions to solve those problems. The module covers topics such as linear programming, integer programming, combinatorial optimisation, modelling and optimisation software, and multi-objective optimisation among others. You will spend around four hours per week in lectures and workshops for this module.
Module Web Links:
Method and Frequency of Class:
|Activity||Number Of Weeks||Number of sessions||Duration of a session|
|Lecture||11 weeks||1 per week||1 hour|
|Workshop||11 weeks||1 per week||2 hours|
|Computing||11 weeks||1 per week||1 hour|
Method of Assessment:
|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|
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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