Total Credits: 20
Level: Level 4
Target Students: Postgraduate students registered in a taught Master course related to computer science or business modelling/optimisation. Computer Science final year undergraduate students and Masters students from other Schools may also take this module (see prerequisites), please contact the module convenor. Available to JYA/Erasmus students.
|Spring||Assessed by end of Spring Semester|
Prerequisites: Considerable knowledge and experience in computer programming. Knowledge of artificial intelligence and optimisation would be an advantage.
Summary of Content: This module explores selected state-of-the-art heuristic search methods (e.g. evolutionary computation and meta-heuristics) and their application to find solutions for complex optimisation and other search problems. The methods studied are selected from the latest specialised research literature. The issues to be studied include: working principles, design and implementation, parameter tuning and experimental testing. Students will achieve awareness of the latest advances in heuristic search methods research and will also implement some of these methods to solve a given problem. This module provides the knowledge and skills to design and implement solution procedures to solve a range of complex problems in industry and business.
Module Web Links:
Method and Frequency of Class:
|Activity||Number Of Weeks||Number of sessions||Duration of a session|
|Lecture||12 weeks||1 per week||1 hour|
|Seminar||12 weeks||1 per week||2 hours|
Method of Assessment:
|Coursework 1||50||Implementation of heuristic search methods|
|Report||25||Progress on coursework|
|Presentation 1||25||Final description of coursework|
Dr D Landa Silva
Education Aims: To provide an in-depth understanding of the issues involved in the design, implementation and asssessment of modern heuristic search methods when applied to complex problems. To have an insight into the latest research on heuristic search methods.
Learning Outcomes: Knowledge and Understanding: State-of-the-art computational heuristic search principles and techniques. Programming of advanced heuristic search methods on modern computers. Intellectual Skills: Ability to work with abstract concepts and in a context of generality. Logical and analytical reasoning. Ability to relate theoretical models to their applications. Professional Skills: Select and apply appropriate methods, models and tools. Communicate results using appropriate styles, conventions and terminology. Transferable Skills: Distillation of key ideas and concepts from critical reading of published literature. Development and communication of novel methods and results.
Offering School: Computer Science
Use the Back facility of your browser to return to the previous page.
Search for another module
Return to The University of Nottingham Welcome Page