Module Specification

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.
1. Module Title Optimisation
2. Module Code COMP557
3. Year Session 2023-24
4. Originating Department Computer Science
5. Faculty Fac of Science & Engineering
6. Semester First Semester
7. CATS Level Level 7 FHEQ
8. CATS Value 15
9. Member of staff with responsibility for the module
Dr F Slivovsky Computer Science F.Slivovsky@liverpool.ac.uk
10. Module Moderator
11. Other Contributing Departments  
12. Other Staff Teaching on this Module
Mrs J Birtall School of Electrical Engineering, Electronics and Computer Science Judith.Birtall@liverpool.ac.uk
13. Board of Studies
14. Mode of Delivery
15. Location Main Liverpool City Campus
    Lectures Seminars Tutorials Lab Practicals Fieldwork Placement Other TOTAL
16. Study Hours 30

  10

      40
17.

Private Study

110
18.

TOTAL HOURS

150
 
    Lectures Seminars Tutorials Lab Practicals Fieldwork Placement Other
19. Timetable (if known)            
 
20. Pre-requisites before taking this module (other modules and/or general educational/academic requirements):

 
21. Modules for which this module is a pre-requisite:

 
22. Co-requisite modules:

 
23. Linked Modules:

 
24. Programme(s) (including Year of Study) to which this module is available on a mandatory basis:

25. Programme(s) (including Year of Study) to which this module is available on a required basis:

26. Programme(s) (including Year of Study) to which this module is available on an optional basis:

27. Aims
 

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

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.

To review the links and interconnections between optimisation and computational complexity theory.

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.

 
28. Learning Outcomes
 

(LO1) The ability to recognise potential research opportunities and research directions

 

(LO2) The ability to read, understand and communicate research literature in the field of optimisation.

 

(LO3) The ability to use appropriate algorithmic paradigms and techniques in context of a particular optimisation model.

 

(LO4) The ability to formulate optimisation models for the purpose of modelling particular applications.

 

(LO5) A critical awareness of current problems and research issues in the field of optimisation.

 

(S1) Critical thinking and problem solving - Critical analysis

 

(S2) Communication (oral, written and visual) - Presentation skills – oral

 
29. Teaching and Learning Strategies
 

Teaching Method 1 - Lectures
Description: Formal Lectures
Teaching Method 2 - Tutorials
Description: Using standard LP solvers, exercises

Standard on-campus delivery
Teaching Method 1 - Lecture
Description: Mix of on-campus/on-line synchronous/asynchronous sessions
Teaching Method 2 - Tutorial
Description: On-campus synchronous sessions

 
30. Syllabus
   

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)

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

Assessment

32. EXAM Duration Timing
(Semester)
% of
final
mark
Resit/resubmission
opportunity
Penalty for late
submission
Notes
  (557) Final exam 150 70
33. CONTINUOUS Duration Timing
(Semester)
% of
final
mark
Resit/resubmission
opportunity
Penalty for late
submission
Notes
  (557.1) Assessment 1 There is a resit opportunity. Standard UoL penalty applies for late submission. This is not an anonymous assessment. Assessment Schedule (When) :Semester 1 0 15
  (557.2) Assessment 2 There is a resit opportunity. Standard UoL penalty applies for late submission. This is not an anonymous assessment. Assessment Schedule (When) :Semester 1 0 15