Postgraduate Course: Applied Decision Optimisation (CMSE11612)
Course Outline
| School | Business School | 
College | College of Arts, Humanities and Social Sciences | 
 
| Credit level (Normal year taken) | SCQF Level 11 (Postgraduate) | 
 
| Course type | Online Distance Learning | 
Availability | Not available to visiting students | 
 
| SCQF Credits | 20 | 
ECTS Credits | 10 | 
 
 
| Summary | This course provides students with the fundamentals of mathematical programming to model and analyse real-world decision problems. | 
 
| Course description | 
    
    Optimisation models frequently appear in business contexts when a manager faces complex decision problems.   
 
Model-based tools to inform managerial decisions have existed for decades, but crucially are continually developing and evolving in line with advances in digital computing.    
 
The objective of this course is not only to develop students' knowledge and understanding of various techniques of prescriptive analytics but also to foster their ability to mathematically formulate business problems and to implement the resulting models on digital platforms using appropriate data. 
 
Content outline: 
 
- Introduction to operational research  
 
- Linear programming  
 
- Integer programming  
 
Student learning experience: 
 
Tutorial/seminar hours represent the minimum total live hours - online - a student can expect to receive on this course. These hours may be delivered in tutorial/seminar, workshop or other interactive whole class or small group format. These live hours may be supplemented by pre-recorded lecture material for students to engage with asynchronously. Live sessions will be delivered only once.
    
    
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Entry Requirements (not applicable to Visiting Students)
| Pre-requisites | 
 | 
Co-requisites |  | 
 
| Prohibited Combinations |  | 
Other requirements |  None | 
 
 
Course Delivery Information
 |  
| Academic year 2024/25, Not available to visiting students (SS1) 
  
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Quota:  None | 
 
| Course Start | 
Semester 2 | 
 
Timetable  | 
	
Timetable | 
| Learning and Teaching activities (Further Info) | 
 
 Total Hours:
200
(
 Lecture Hours 10,
 Seminar/Tutorial Hours 20,
 Programme Level Learning and Teaching Hours 4,
Directed Learning and Independent Learning Hours
166 )
 | 
 
| Assessment (Further Info) | 
 
  Written Exam
0 %,
Coursework
100 %,
Practical Exam
0 %
 | 
 
 
| Additional Information (Assessment) | 
40% Class Test (Individual)  - Assesses Learning Outcomes 1-4 
60% Project report (Individual) - Assesses Learning Outcomes 1-4 | 
 
| Feedback | 
Formative: Delivered throughout live sessions (Q&A). 
 
Summative: Written feedback is provided on the two pieces of assessment. 
 
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| No Exam Information | 
 
Learning Outcomes 
    On completion of this course, the student will be able to:
    
        - Demonstrate sound knowledge and critical understanding of various prescriptive analytics techniques.
 - Demonstrate abilities to analyse the business problems in the selected domains and to implement appropriate prescriptive analytics techniques to obtain a meaningful solution.
 - Utilise computer programming and optimisation solver to support computer-based prescriptive analytics.
 -  Interpret solutions, formulate managerial guidelines, and make recommendations to a critical audience of specialists and the general public.
 
     
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Reading List 
Lieberman, Gerald J., and Frederick S. Hillier.Introduction to operations research. Vol. 11. New York, NY, USA: McGraw-Hill, 2021 
 
Cooper, W. W. Data envelopment analysis a comprehensive text with models, applications, references and DEA-solver software. 2nd edition. New York: Springer. |   
 
Additional Information
| Graduate Attributes and Skills | 
Cognitive Skills 
 
After completing this course, students should be able to: 
 
Understand how to manage and sustain successful individual and group relationships in order to achieve 
positive and responsible outcomes, in a range of virtual and face-to-face environments. 
 
Be self-motivated; curious; show initiative; set, achieve and surpass goals; as well as demonstrating 
adaptability, capable of handling complexity and ambiguity, with a willingness to learn; as well as being able to 
demonstrate the use digital and other tools to carry out tasks effectively, productively, and with attention to 
quality. 
 
Knowledge and Understanding 
 
After completing this course, students should be able to: 
 
Demonstrate a thorough knowledge and understanding of contemporary organisational disciplines; 
comprehend the role of business within the contemporary world; and critically evaluate and synthesise primary 
and secondary research and sources of evidence in order to make, and present, well informed and transparent 
organisation-related decisions, which have a positive global impact. 
 
Identify, define and analyse theoretical and applied business and management problems, and develop 
approaches, informed by an understanding of appropriate quantitative and/or qualitative techniques, to explore 
and solve them responsibly. 
 
Practice: Applied Knowledge, Skills and Understanding 
 
After completing this course, students should be able to: 
 
Apply creative, innovative, entrepreneurial, sustainable and responsible business solutions to address 
social, economic and environmental global challenges. 
 
Communication, ICT, and Numeracy Skills 
 
After completing this course, students should be able to: 
 
Critically evaluate and present digital and other sources, research methods, data and information; discern 
their limitations, accuracy, validity, reliability and suitability; and apply responsibly in a wide variety of 
organisational contexts. | 
 
| Keywords | Not entered | 
 
 
Contacts 
| Course organiser | Dr Xin Fei 
Tel: (0131 6)50 8074 
Email: Xin.Fei@ed.ac.uk | 
Course secretary | Mr Ewan Henderson 
Tel:  
Email: ehende2@ed.ac.uk | 
   
 
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