University Homepage
DRPS Homepage
DRPS Search
DRPS Contact
DRPS : Course Catalogue : School of Mathematics : Mathematics

Undergraduate Course: Linear Programming, Modelling and Solution (MATH10073)

Course Outline
SchoolSchool of Mathematics CollegeCollege of Science and Engineering
Credit level (Normal year taken)SCQF Level 10 (Year 3 Undergraduate) AvailabilityAvailable to all students
SCQF Credits10 ECTS Credits5
SummaryLinear programming (LP) is the fundamental modelling technique in optimal decision-making. This course will introduce the concepts of LP modelling, explore the mathematical properties of general LP problems and study the theory of the simplex algorithm as a solution technique. Students will use the Xpress mathematical programming system to create, solve and analyse case studies and then present their work in oral and written form. As a consequence, in addition to the assessment of theoretical understanding and hand calculation via a closed book examination, the course is also assessed via an Xpress class test and group-based case study.
Course description Linear programming (LP) offers the natural entry to the study of operational research, not only because LP is the fundamental modelling technique in optimal decision-making, but also because the mathematical nature of LP problems [everything is linear!] means that they can be analysed with tools from linear algebra introduced at level 8. This course introduces the concepts of LP modelling, explores the mathematical properties of general LP problems and studies the theory of the simplex algorithm as a solution technique. The novel feature of this course is that it introduces the Xpress mathematical programming system to create, solve and analyse case studies. The course ends with a group-based case study in which, much like an OR consultant might do, you will model, solving and analyse a meaningful example, presenting your work in oral and written form.


1. Linear programming: Decision variables, objective function, bounds and constraints. The feasible region; geometric and algebraic characterisation of an optimal solution. The dual of an LP problem and duality theory. Theory underlying sensitivity and fair prices.

2. Modelling: Introduction to the Xpress mathematical programming system as a means of modelling, solving and analysing LP case studies. Exploration of the modelling language Mosel to define index sets, data arrays, decision variables, constraints, solve LP problems, analyse problem sensitivity and report the results in a suitable format for further processing using Excel.

3. Solution: Study of the simplex algorithm for LP problems. Geometric and algebraic concepts underlying the algorithm and consequences for solution methods. Proof of termination for non-degenerate LPs. Linear algebra underlying its implementation via the revised simplex method.
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Co-requisites
Prohibited Combinations Students MUST NOT also be taking Methodology, Modelling and Consulting Skills (MATH11007)
Other requirements None
Information for Visiting Students
Pre-requisitesPrevious study of linear algebra: matrix (non-)singularity, linear systems of equations, matrix-matrix multiplication.
High Demand Course? Yes
Course Delivery Information
Academic year 2017/18, Available to all students (SV1) Quota:  None
Course Start Semester 2
Timetable Timetable
Learning and Teaching activities (Further Info) Total Hours: 100 ( Lecture Hours 15, Seminar/Tutorial Hours 5, Supervised Practical/Workshop/Studio Hours 10, Summative Assessment Hours 2, Programme Level Learning and Teaching Hours 2, Directed Learning and Independent Learning Hours 66 )
Assessment (Further Info) Written Exam 50 %, Coursework 50 %, Practical Exam 0 %
Additional Information (Assessment) Coursework 50%, Examination 50%
Feedback Not entered
Exam Information
Exam Diet Paper Name Hours & Minutes
Main Exam Diet S2 (April/May)MATH10073 Linear Programming, Modelling and Solution1:30
Learning Outcomes
On completion of this course, the student will be able to:
  1. Ability to model, solve and analyse a simple case study using Xpress and present an investigation of that case study in oral and written form.
  2. Understanding of the mathematical theory underlying LP and the simplex algorithm as a method of solution.
Reading List
Introduction to Operations Research, F. S. Hillier and G. Lieberman, McGraw-Hill Higher Education, 9th edition. ISBN-10: 0071267670
Additional Information
Graduate Attributes and Skills Experience of modelling realistic case studies. Further development of programming skills (using Mosel), group-work, verbal and oral presentation skills.
Additional Class Delivery Information 16 one-hour lectures
5 one-hour workshops
4 two-hour labs
KeywordsLPMS,linear programming,modelling language,case study
Course organiserDr Julian Hall
Tel: (0131 6)50 5075
Course secretaryMs Hannah Burley
Tel: (0131 6)50 4885
Help & Information
Search DPTs and Courses
Degree Programmes
Browse DPTs
Humanities and Social Science
Science and Engineering
Medicine and Veterinary Medicine
Other Information
Combined Course Timetable
Important Information