Undergraduate Programme and Module Handbook 2020-2021 (archived)
Module MATH3141: OPERATIONS RESEARCH III
Department: Mathematical Sciences
MATH3141: OPERATIONS RESEARCH III
| Type | Open | Level | 3 | Credits | 20 | Availability | Available in 2020/21 | Module Cap | Location | Durham |
|---|
Prerequisites
- Calculus and Probability I (MATH1061) and Linear Algebra I (MATH1071).
Corequisites
- None.
Excluded Combination of Modules
- None.
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.
Learning Outcomes
Subject-specific Knowledge:
- Ability to solve novel and/or complex problems in Operations Research.
- Systematic and coherent understanding of the theoretical mathematics underlying Operations Research.
- A coherent body of knowledge, 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; finite state Markov chains; deterministic and probabilistic dynamic programming; Markov decision processes, including policy-improvement algorithms; inventory theory. .
Subject-specific Skills:
- Specialised mathematical skills which can be used with minimal guidance in the following areas: Modelling, Computation.
Key Skills:
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 | 42 | 2 per week for 20 weeks and 2 in term 3 | 1 Hour | 42 | |
| Problems Classes | 8 | Four in each of terms 1 and 2 | 1 Hour | 8 | |
| Preparation and Reading | 150 | ||||
| Total | 200 |
Summative Assessment
| Component: Examination | Component Weighting: 90% | ||
|---|---|---|---|
| Element | Length / duration | Element Weighting | Resit Opportunity |
| Written examination | 3 Hours | 100% | |
| Component: Continuous Assessment | Component Weighting: 10% | ||
| Element | Length / duration | Element Weighting | Resit Opportunity |
| Eight written assignments to be assessed and returned. Other assignments are set for self-study and complete solutions are made available to students. | 100% | ||
Formative Assessment:
■ 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