Overview
- Start dateSeptember
- DurationMSc: one year full-time, up to three years part-time; PgDip: up to one year full-time, up to two years part-time; PgCert: up to one year full-time, up to two years part-time
- DeliveryAssessment is 50% by coursework, 10% by exam and 40% thesis/dissertation
- QualificationMSc, PgDip, PgCert
- Study typeFull-time / Part-time
- CampusCranfield University at Shrivenham
Who is it for?
The course is suitable for both military and civilian personnel, including those from defence industry and government departments.
10 places are normally available for the full-time cohort.
Why this course?
The course provides a detailed exposure to the context, issues and methods used to analyse the increasingly complex problems which are found in the defence environment and to support decision making. It exposes the types of analysis and allows practical experience of tools and methods which are used, ranging from judgemental analysis through mathematical techniques to models and simulations. The course includes judgemental elicitation and analysis techniques, mathematical analysis methods (including optimisation), war gaming and combat modelling, logistics modelling and simulation methods. The use and utility of all the methods are explored through practical exercises and studies.
On successful completion of the course you will:
- Demonstrate a thorough understanding of the methods, techniques and tools for modelling defence problems and systems;
- Be able to critically assess a range of approaches and methods to help support defence analysis and decision making.
Informed by industry
The aim of the Industrial Advisory Panel, which is common to all components of the AMOR Postgraduate Suite, is to offer advice and input to the Course Director and the teaching team in terms of curriculum content, acquisition skills and other attributes that the practitioner community may be seeking from graduates of the course. Currently the Industrial Advisory Panel for this programme has members on it from both the defence industry and the MoD.
Course details
MSc students must complete a taught phase consisting of 12 standard modules, which includes two core modules (Introduction to Operational Research Techniques and Decision Analysis), plus four advanced modules, followed by an individual thesis in a relevant topic.
Thesis topics will be related to problems of specific interest to students and sponsors or local industry wherever possible. PgDip students are required to undertake the same taught phase as the MSc, but without the individual thesis. PgCert students must complete the core module (Introduction to Operational Research Techniques) together with five other modules; up to three of these may be advanced modules.
Course delivery
Assessment is 50% by coursework, 10% by exam and 40% thesis/dissertation
Individual project
An individual research project on an agreed topic that allows you to demonstrate your technical expertise, independent learning abilities and critical appraisal skills.
Modules
Keeping our courses up-to-date and current requires constant innovation and change. The modules we offer reflect the needs of business and industry and the research interests of our staff and, as a result, may change or be withdrawn due to research developments, legislation changes or for a variety of other reasons. Changes may also be designed to improve the student learning experience or to respond to feedback from students, external examiners, accreditation bodies and industrial advisory panels.
To give you a taster, we have listed the compulsory and elective (where applicable) modules which are currently affiliated with this course. All modules are indicative only, and may be subject to change for your year of entry.
Course modules
Compulsory modules
All the modules in the following list need to be taken as part of this course.
Introductory Studies
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Aim |
To prepare you mathematically and organisationally to study at CDS on the Defence Simulation and Modelling and Military Operational Research Postgraduate programs. |
Syllabus |
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Intended learning outcomes |
On successful completion of this module you will be able to:
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Introduction to Operational Research Techniques
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Syllabus |
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Intended learning outcomes |
On successful completion of this module you will be able to:
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Discrete and Continuous Simulation
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The aim of the course is to provide you with a good understanding of the principles underlying both discrete event simulation (DES) and continuous simulation, focusing, in the latter case, on System Dynamics (SD) modelling. |
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Intended learning outcomes |
On successful completion of this module you will be able to:
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Decision Analysis
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Syllabus |
• Introduction: the role and scope of decision analysis in supporting decision making.
• Pay-off Matrices: structuring decision problems using a pay- off matrix to represent the value or utility of each option for each possible state of nature. Analysing the pay-off matrix under conditions of uncertainty and risk. Sensitivity/robustness of decisions to the inputs. • Decision Trees: structuring and analysing decision problems using a decision tree to represent sequential decision making under conditions of risk and uncertainty. The application of Bayes’Theorem to update probabilities in the light of new information. The calculation of the value of perfect and imperfect information. • Bayesian Networks and Influence Diagram Decision Networks: these modern tools are examples of probabilistic graphical models which offer a powerful framework for reasoning and decision-making under risk and uncertainty. Modelling assumptions and development, example applications and software. • Game Theory: classical two person zero sum game theory and its application to decision making under conditions of competition or conflict. Extensions of the classical theory to non-zero sum games. • Judgmental Methods: the elicitation and analysis of individual judgements; the nature and effects of various cognitive biases affecting judgement. • Problem Structuring Methods: a review and brief introduction to some of the ‘softer’ methods used to support decision makers. The topics covered will include the Strategic Choice Approach, scenario planning, cognitive mapping and approaches to strategic decision making. • Multiple Criteria Decision Analysis: a review of the different approaches used in multiple criteria decision analysis where several, often conflicting, criteria are important to a decision-maker: aggregate value methods to permit trade-offs in multiple attribute decision making and mathematical programming methods in multiple objective decision making. • Software for Decision Analysis: throughout the course reference will be made to the application of decision analysis software to help support the decision making process, including demonstrations and hands-on practicals. |
Intended learning outcomes |
On successful completion of this module a student should be able to: • structure decision problems using a pay-off matrix and analyse the pay- off matrix under conditions of uncertainty, risk and competition, • structure and analyse sequential decision problems using a decision tree, • structure and analyse decision problems using Bayesian networks and influence diagram decision networks, • structure and analyse decision problems based on using expert judgments, • explain and apply the different approaches used in multiple criteria decision analysis, • explain how the different methods of representing decision problems can be used to support defence decision-making. |
War Gaming and Combat Modelling
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Intended learning outcomes |
On successful completion of this module you will be able to:
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Statistical Analysis and Trials
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Aim |
To give you an introduction to probability distributions, the design of experiments and the analysis of data. |
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Intended learning outcomes |
On successful completion of this module you will be able to:
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Weapon System Performance Assessment
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Aim |
To enable you to understand the application of operational research techniques to the assessment of weapon systems. |
Syllabus |
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Intended learning outcomes |
On successful completion of this module you will be able to:
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Intelligent Systems
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The aim of this module is to provide you with basic knowledge of intelligent systems techniques that can be applied in a variety of disciplines. |
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Syllabus |
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Intended learning outcomes |
On successful completion of this module you will be able to:
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Logistics Modelling
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Aim |
The aim of the module is to provide you with a good understanding of the principles and techniques of Logistics Modelling. The emphasis is on the development and application of quantitative models to support logistical decision-making. |
Syllabus |
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Intended learning outcomes |
On successful completion of this module you will be able to:
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Advanced Module 1
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The aim of this module is to allow students to conduct an in-depth study in an area of particular personal interest or relevance to them, in the context of their degree. |
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Syllabus |
A self-study ‘mini-project’ conducted over two weeks, on an individually selected and agreed topic, which must follow on from one or more already completed standard taught modules in that degree. Part-time students will typically complete their work over a 10-week period, one such block of 10 weeks being offered in each academic term. |
Intended learning outcomes |
On successful completion of the module a diligent student will be able, within the individual topic agreed, to:
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Advanced Module 2
Aim |
The aim of this module is to allow students to conduct an in-depth study in an area of particular personal interest or relevance to them, in the context of their degree. |
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Syllabus |
A self-study ‘mini-project’ conducted over two weeks, on an individually selected and agreed topic, which must follow on from one or more already completed standard taught modules in that degree. Part-time students will typically complete their work over a 10-week period, one such block of 10 weeks being offered in each academic term. |
Intended learning outcomes |
On successful completion of the module a diligent student will be able, within the individual topic agreed, to:
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Advanced Module 3
Aim |
The aim of this module is to allow students to conduct an in-depth study in an area of particular personal interest or relevance to them, in the context of their degree. |
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Syllabus |
A self-study ‘mini-project’ conducted over two weeks, on an individually selected and agreed topic, which must follow on from one or more already completed standard taught modules in that degree. Part-time students will typically complete their work over a 10-week period, one such block of 10 weeks being offered in each academic term. |
Intended learning outcomes |
On successful completion of the module a diligent student will be able, within the individual topic agreed, to:
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Advanced Module 4
Aim |
The aim of this module is to allow students to conduct an in-depth study in an area of particular personal interest or relevance to them, in the context of their degree. |
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Syllabus |
A self-study ‘mini-project’ conducted over two weeks, on an individually selected and agreed topic, which must follow on from one more already completed standard taught modules in that degree. Part-time students will typically complete their work over a 10-week period. One such block of 10 weeks being offered in each academic term. |
Intended learning outcomes |
On successful completion of the module a diligent student will be able, within the individual topic agreed, to:
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Teaching team
You will be taught by Cranfield's leading experts with capability expertise, industry knowledge and collective subject research, as well as external speakers from industry and defence. The Student Academic Support lead for the MSc in Military Operational Research is Karen Crouch and the Course Director is Jonathan Searle. The teaching team includes:
Your career
The course equips you for appointments within the armed forces or government, or in the defence related activities of commercial organisations, or further research leading to a PhD.
How to apply
Click on the ‘Apply now’ button below to start your online application.
See our Application guide for information on our application process and entry requirements.