Catalogue of Modules, University of Nottingham

G54HSM Heuristic Search Methods
(Last Updated:03 May 2017)

Year  09/10

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.

Taught Semesters:

SemesterAssessment
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.

Corequisites:  None.

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:
   
  • Module Web Page
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  • Reading List
  • Method and Frequency of Class:

    ActivityNumber Of WeeksNumber of sessionsDuration of a session
    Lecture 12 weeks1 per week1 hour
    Seminar 12 weeks1 per week2 hours

    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
    Coursework 1 50 Implementation of heuristic search methods 
    Report 25 Progress on coursework 
    Presentation 1 25 Final description of coursework 

    Convenor: 
    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


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