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 OPERATIONAL RESEARCH: PROBABILISTIC MODELS
2. Module Code MATH268
3. Year Session 2023-24
4. Originating Department Mathematical Sciences
5. Faculty Fac of Science & Engineering
6. Semester First Semester
7. CATS Level Level 5 FHEQ
8. CATS Value 15
9. Member of staff with responsibility for the module
Dr R Tatar Mathematical Sciences Radu.Tatar@liverpool.ac.uk
10. Module Moderator
11. Other Contributing Departments  
12. Other Staff Teaching on this Module
Dr SA Fairfax Mathematical Sciences Simon.Fairfax@liverpool.ac.uk
Dr G Zheng Mathematical Sciences Guangqu.Zheng@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 36

  12

      48
17.

Private Study

102
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 introduce a range of models and techniques for solving under uncertainty in Business, Industry, and Finance.

 
28. Learning Outcomes
 

(LO1) The ability to understand and describe mathematically real-life optimization problems.

 

(LO2) Understanding the basic methods of dynamical decision making.

 

(LO3) Understanding the basics of forecasting and simulation.

 

(LO4) The ability to analyse elementary queueing systems.

 

(S1) Problem solving skills

 

(S2) Numeracy

 
29. Teaching and Learning Strategies
 

Material is presented during lectures (3 hours per week). Tutorials (1 hour per week) are used for consolidation and practice, and for help with individual questions.

 
30. Syllabus
   

Decision analysis: strategies and decision trees. Markov Decision Processes. Forecasting: Queuing Theory: M/M/1, M/M/K and similar Markov models. Simulation: pseudo-random generators, universal and special algorithms (Polar, Von Neumann, etc). Simulation of stochastic processes including queues.

 
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
  final assessment on campus There is a resit opportunity. This is an anonymous assessment. 60 50
33. CONTINUOUS Duration Timing
(Semester)
% of
final
mark
Resit/resubmission
opportunity
Penalty for late
submission
Notes
  Homework assignment 1 Standard UoL penalty applies for late submission. This is not an anonymous assessment. 0 10
  Homework assignment 2 Standard UoL penalty applies for late submission. This is not an anonymous assessment. 0 10
  Homework assignment 5 Standard UoL penalty applies for late submission. This is not an anonymous assessment. 0 10
  Homework assignment 3 Standard UoL penalty applies for late submission. This is not an anonymous assessment. 0 10
  Homework assignment 4 Standard UoL penalty applies for late submission. This is not an anonymous assessment. 0 10