|Last Update: 30 April 2018|
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Linear and Discrete Optimization (G54LDO)
The information here corresponds to Semester 1 of the session 2017-2018. Please note that the previous version of G54LDO, the module Operations Research and Optimisation (G54ORM), is now discontinued.
See the Module
See the Reading List.
IMPORTANT: The first teaching event of this module is the Lecture session on Tuesday 3-October-2017 from 14-16 hrs in room A25 of the Business School South Building. The first Workshop on Thursday 5-October will include an activity for those that are already enrolled in the module or are considering taking this module. I will also be available to answer questions about the module during this first Lecture and Workshop sessions.
If you are considering taking this module in your course, but need more information to make your decision, you are very welcome to join the first lecture which will give you a good idea about the topics in the module and the type of assessment in this module including sample of past students work and feedback. Alternatively, please contact me if you want to know more about the module.
CONTEXT: This module is related to other modules in the theme 'AI, Modelling and Optimization' in the School of Computer Science. For example, it is closely related to the G52AIM module. In the G54LDO module we learn how to write an solve mathematical models of optimization problems like bin packing and travelling salesman. When the problem is not too large, mathematical optimization can be used to find the actual optimal solution to the problem. But when the problem is too large, these mathematical optimization methods might take too long time and hence other search techniques like those studies in the module G52AIM (heuristics) can be used. However, those heuristic search techniques cannot guarantee to find the actual optimal solution to the problem, but a good enough quality solution is shorter computation times. The techniques studied in the G54LDO module are the base for developing and understanding optimization and is core knowledge for anyone interested in this field. Even if you are developing heurisitcs, it is essential to understand mathematical optimization.
Linear and Discrete Optimization, the topic of this module, are techniques within the wider field of Operations Research, to get an idea see this video and this web page. Also, here there is a sample of the lecture notes. You might also want to read this student's reflection about operations research.
Read about how Google uses Optimization and other Advanced Analytics techniques in order to achieve their mission.
This postgraduate module looks into modelling and optimization techniques, covering the understanding and development of formal optimization models and then developing the computational solutions using existing solvers and/or computer programming for solving real-world operational problems.
This page gives only an overview of the module. All the materials including lecture notes, coursework, feedback, etc. are available on the Moodle Learning Enviroment for students enrolled in the module.
Content of the Module:
The module covers the following topics: Linear Programming, Modelling and Optimization Software, Post-optimality Analysis, Integer Programming, Mathematical Programming Modelling Techniques, Multi-objective Optimization, Algorithms for LP and IP Models, Dynamic Programming.
The exam is based on problem modelling and solving, more details will be given during the lectures.
The coursework involves the modelling and solution of real-world optimization problems.
Inclass Exam (25%)
Series of weekly online tests based on the workshops of the module.