MA205-5-SP-CO:
Optimisation (Linear Programming)
2024/25
Mathematics, Statistics and Actuarial Science (School of)
Colchester Campus
Spring
Undergraduate: Level 5
Current
Monday 13 January 2025
Friday 21 March 2025
15
26 September 2024
Requisites for this module
MA114
(none)
MA114
(none)
MA305, MA306
BSC N233 Actuarial Science (Including Placement Year),
BSC N323 Actuarial Science,
BSC N323DF Actuarial Science,
BSC N324 Actuarial Science (Including Year Abroad),
BSC N325 Actuarial Science (Including Foundation Year),
BSC L1G1 Economics with Mathematics,
BSC L1G3 Economics with Mathematics (Including Placement Year),
BSC L1G8 Economics with Mathematics (Including Foundation Year),
BSC L1GC Economics with Mathematics (Including Year Abroad),
BSC 5B43 Statistics (Including Year Abroad),
BSC 9K12 Statistics,
BSC 9K13 Statistics (Including Placement Year),
BSC 9K18 Statistics (Including Foundation Year),
BSC G1G4 Mathematics with Computing (Including Year Abroad),
BSC G1G8 Mathematics with Computing (Including Foundation Year),
BSC G1GK Mathematics with Computing,
BSC G1IK Mathematics with Computing (Including Placement Year),
BSC I1G3 Data Science and Analytics,
BSC I1GB Data Science and Analytics (Including Placement Year),
BSC I1GC Data Science and Analytics (Including Year Abroad),
BSC I1GF Data Science and Analytics (Including Foundation Year),
MSCIN399 Actuarial Science and Data Science,
BSC N333 Actuarial Studies,
BSC N334 Actuarial Studies (Including Placement Year),
BSC N335 Actuarial Studies (Including Year Abroad)
An introduction to the methods of linear programming, including both theoretical and computational aspects.
The aims of this module are:
- To introduce students to the theory and practice of Linear Programming (LP), which deals with problems that involve the maximising or minimising of a linear function, subject to linear constraints on the variables.
- To provide students competence in developing mathematical optimisation modelling, and proposing suitable solutions.
By the end of the module, students will be expected to be able to:
- Formulate an appropriate linear programming model, from a written description of a problem environment, whose solution would actually solve the problem.
- Recognise the scope and limitations of linear programming modelling and appreciate its position within the Operational Research discipline.
- Solve any (small) linear programming problem using an appropriate version of the Simplex Algorithm.
- Perform sensitivity analysis on an optimal solution.
- Use Duality Theory to prove basic theorems of Linear Programming and apply Duality Theory to recognize optimality, infeasibility or unboundedness in a linear program.
- Outline the Transportation Simplex Algorithm and find basic feasible solutions.
Indicative syllabus:
Formulation of linear programming models
Graphical solution
The Simplex Algorithm, Two-Phase Simplex and Revised Simplex
Duality, Complementary Slackness and Dual Simplex
Sensitivity Analysis
Transportation Problem
Teaching in the School will be delivered using a range of face-to-face lectures, classes, and lab sessions as appropriate for each module. Modules may also include online only sessions where it is advantageous, for example for pedagogical reasons, to do so.
This module does not appear to have any essential texts. To see non - essential items, please refer to the module's
reading list.
Assessment items, weightings and deadlines
| Coursework / exam |
Description |
Deadline |
Coursework weighting |
| Coursework |
Assignment 1 |
21/02/2025 |
|
| Coursework |
Assignment 2 |
21/03/2025 |
|
| Exam |
Main exam: In-Person, Open Book (Restricted), 120 minutes during Summer (Main Period)
|
| Exam |
Reassessment Main exam: In-Person, Open Book (Restricted), 120 minutes during September (Reassessment Period)
|
Exam format definitions
- Remote, open book: Your exam will take place remotely via an online learning platform. You may refer to any physical or electronic materials during the exam.
- In-person, open book: Your exam will take place on campus under invigilation. You may refer to any physical materials such as paper study notes or a textbook during the exam. Electronic devices may not be used in the exam.
- In-person, open book (restricted): The exam will take place on campus under invigilation. You may refer only to specific physical materials such as a named textbook during the exam. Permitted materials will be specified by your department. Electronic devices may not be used in the exam.
- In-person, closed book: The exam will take place on campus under invigilation. You may not refer to any physical materials or electronic devices during the exam. There may be times when a paper dictionary,
for example, may be permitted in an otherwise closed book exam. Any exceptions will be specified by your department.
Your department will provide further guidance before your exams.
Overall assessment
Reassessment
Module supervisor and teaching staff
Dr Felipe Maldonado, email: felipe.maldonado@essex.ac.uk.
Dr Felipe Maldonado & Dr T. Al-Karhi
maths@essex.ac.uk
Yes
Yes
No
Dr Yinghui Wei
University of Plymouth
Dr Murray Pollock
Newcastle University
Director of Statistics / Senior Lecturer
Available via Moodle
Of 33 hours, 33 (100%) hours available to students:
0 hours not recorded due to service coverage or fault;
0 hours not recorded due to opt-out by lecturer(s).
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