Undergraduate Programme and Module Handbook 2013-2014 (archived)
Module MATH4251: OPERATIONS RESEARCH IV
Department: Mathematical Sciences
MATH4251:
OPERATIONS RESEARCH IV
Type |
Open |
Level |
4 |
Credits |
20 |
Availability |
Not available in 2013/14 |
Module Cap |
None. |
Location |
Durham
|
Prerequisites
- Core Mathematics A (MATH 1012) AND a minimum of 40 credits
of Mathematics modules at Level 3.
Corequisites
Excluded Combination of Modules
- Operations Research III (MATH3141)
Aims
- To introduce some of the central mathematical models and methods of
operations research.
Content
- Introduction to Operations Research.
- Linear programming: primal/dual simplex algorithm,
sensitivity analysis, transportation algorithm.
- Optimisation on networks.
- Introduction to Markov chains.
- Inventory theory.
- Markov decision processes.
- Further topics chosen from: integer programming, iterative
non linear programming, dynamic programming.
- Reading material on a topic related to: integer
programming, queueing theory.
Learning Outcomes
- By the end of the module students will: be able to solve
novel and/or complex problems in Operations Research.
- have a systematic and coherent understanding of theoretical
mathematics in the fields Operations Research.
- have acquired coherent body of knowledge of these subjects
demonstrated through one or more of the following topic areas: Linear
programming and the simplex algorithm.
- Duality and sensitivity analysis for L.P.
- Optimisation on network models.
- Brief treatment of finite state Markov chains.
- Deterministic and probabilistic dynamic
programming.
- Markov decision processes, including policy-improvement
algorithms.
- Inventory Theorem.
- Knowledge and understanding of a topic in the following
areas: integer programming, queueing theory.
- In addition students will have specialised mathematical
skills in the following areas which can be used with minimal guidance:
Modelling, Computation.
Modes of Teaching, Learning and Assessment and how these contribute to
the learning outcomes of the module
- Lectures demonstrate what is required to be learned and the
application of the theory to practical examples.
- Assignments for self-study develop problem-solving skills and
enable students to test and develop their knowledge and
understanding.
- Formatively assessed assignments provide practice in the
application of logic and high level of rigour as well as feedback for
the students and the lecturer on students' progress.
- The end-of-year examination assesses the knowledge acquired
and the ability to solve predictable and unpredictable
problems.
Teaching Methods and Learning Hours
Activity |
Number |
Frequency |
Duration |
Total/Hours |
|
Lectures |
40 |
2 per week for 19 weeks and 2 in term 3 |
1 Hour |
40 |
|
Preparation and Reading |
|
|
|
160 |
|
Total |
|
|
|
200 |
|
Summative Assessment
Component: Examination |
Component Weighting: 100% |
Element |
Length / duration |
Element Weighting |
Resit Opportunity |
three hour written examination |
|
100% |
|
Four written assignments to be assessed and
returned. Other assignments are set for self-study and complete solutions
are made available to students.
■ Attendance at all activities marked with this symbol will be monitored. Students who fail to attend these activities, or to complete the summative or formative assessment specified above, will be subject to the procedures defined in the University's General Regulation V, and may be required to leave the University