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DRPS : Course Catalogue : Business School : Common Courses (Management School)

Postgraduate Course: Applied Decision Optimisation (CMSE11612)

Course Outline
SchoolBusiness School CollegeCollege of Arts, Humanities and Social Sciences
Credit level (Normal year taken)SCQF Level 11 (Postgraduate)
Course typeOnline Distance Learning AvailabilityNot available to visiting students
SCQF Credits20 ECTS Credits10
SummaryThis 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.
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Co-requisites
Prohibited Combinations Other requirements None
Course Delivery Information
Academic year 2023/24, Not available to visiting students (SS1) 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.

No Exam Information
Learning Outcomes
On completion of this course, the student will be able to:
  1. Demonstrate sound knowledge and critical understanding of various prescriptive analytics techniques.
  2. Demonstrate abilities to analyse the business problems in the selected domains and to implement appropriate prescriptive analytics techniques to obtain a meaningful solution.
  3. Utilise computer programming and optimisation solver to support computer-based prescriptive analytics.
  4. Interpret solutions, formulate managerial guidelines, and make recommendations to a critical audience of specialists and the general public.
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

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.
KeywordsNot entered
Course organiserDr Xin Fei
Tel: (0131 6)50 8074
Course secretaryMs Heather Ferguson
Tel: (0131 6)50 8074
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