Module Details
The information contained in this module specification was correct at the time of publication but may be subject to change, either during the session because of unforeseen circumstances, or following review of the module at the end of the session. Queries about the module should be directed to the member of staff with responsibility for the module.
Title OPTIMISATION
Code COMP557
Coordinator Dr M Gairing
Computer Science
M.Gairing@liverpool.ac.uk
Year CATS Level Semester CATS Value
Session 2016-17 Level 7 FHEQ First Semester 15

Aims
  • To provide a foundation for modelling various continuous and discrete optimisation problems.

    1. To provide the tools and paradigms for the design and analysis of algorithms for continuous and discrete optimisation problems. Apply these tools to real-world problems.

    2. To review the links and interconnections between optimisation and computat ional complexity theory.

    3. To provide an in-depth, systematic and critical understanding of selected significant topics at the intersection of optimisation, algorithms and (to a lesser extent) complexity theory, together with the related research issues.


    • Learning Outcomes
    A critical awareness of current problems and research issues in the field of optimisation.

    The ability to formulate optimisation models for the purpose of modelling particular applications.

    The ability to use appropriate algorithmic paradigms and techniques in context of a particular optimisation model.

    The ability to read, understand and communicate research literature in the field of optimisation.

    The ability to recognise potential research opportunities and research directions.


    Syllabus
    1 

    Basics: Linear Algebra, Geometry and Graph Theory. (5 lectures)

    Linear Programming Basics: Introduction, Definitions, Examples, Geometric and Algebraic views of Linear Programming, Mixed Integer Linear Programming (7 lectures)

    Linear Programming: Simplex Algorithm (6 lecture)

    Linear Programming: Duality (5 lectures )

    Algorithms for important optimisation problems (e.g. optimal trees and paths, network flows). (7 lectures)

    Teaching and Learning Strategies

    Lectures - Formal Lectures

    Tutorials - Using standard LP solvers, exercises

    Teaching Schedule
      Lectures Seminars Tutorials Lab Practicals Fieldwork Placement Other TOTAL
    Study Hours           10
    Using standard LP solvers, exercises
    30
    Formal Lectures
    		40
    Timetable (if known)              
    Private Study 110
    TOTAL HOURS 150

    Assessment
    EXAM Duration Timing
    (Semester)    		 % of
    final
    mark    		 Resit/resubmission
    opportunity    		 Penalty for late
    submission    		 Notes
    Unseen Written Exam  150  Semester 1  75  Yes  Standard UoL penalty applies  Final Exam Notes (applying to all assessments) 2 (sets of) assessment tasks This work is not marked anonymously. Written examination  
    CONTINUOUS Duration Timing
    (Semester)    		 % of
    final
    mark    		 Resit/resubmission
    opportunity    		 Penalty for late
    submission    		 Notes
    Coursework  2 sets of assessment  Semester 1  15  No reassessment opportunity  Standard UoL penalty applies  Assessment 1 There is no reassessment opportunity, Resit exam only. 
    Coursework  2 sets of assessment  Semester 1  10  No reassessment opportunity  Standard UoL penalty applies  Assessment 2 There is no reassessment opportunity, Resit exam only. 

    Recommended Texts
    Reading lists are managed at readinglists.liverpool.ac.uk. Click here to access the reading lists for this module.
    Explanation of Reading List: