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Module Detailed Information for [MA3252]
Academic Year : 2017/2018 Semester : 2
Correct as at 19 Jan 2018 05:00

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Module Information
Module Code :
Module Title : Linear and Network Optimisation
Module Description : The objective of this course is to work on optimization problems which can be formulated as linear and network optimization problems. We formulate linear programming (LP) problems and solve them by the simplex method (algorithm). We also look at the geometrical aspect and develop the mathematical theory of the simplex method. We further study problems which may be formulated using graphs and networks. These optimization problems can be solved by using linear or integer programming approaches. However, due to its graphical structure, it is easier to handle these problems by using network algorithmic approaches. Applications of LP and network optimization will be demonstrated. This course should help the student in developing confidence in solving many similar problems in daily life that require much computing. Major topics: Introduction to LP: solving 2-variable LP via graphical methods. Geometry of LP: polyhedron, extreme points, existence of optimal solution at extreme point. Development of simplex method: basic solution, reduced costs and optimality condition, iterative steps in a simplex method, 2-phase method and Big-M method. Duality: dual LP, duality theory, dual simplex method. Sensitivity Analysis. Network optimization problems: minimal spanning tree problems, shortest path problems, maximal flow problems, minimum cost flow problems, salesman problems and postman problems.
Module Examinable : -
Exam Date : 08-05-2018 EVENING
Modular Credits : 4
Pre-requisite : MA1101R or MA1306 or MA1311 or MA1508 or MA1506 or MA1508E or MA1513
Preclusion : MQ2204, CS3252, IC2231, DSC3214, DSN3701, MA3235, BH3214, ISE students
Module Workload (A-B-C-D-E)* : 3-1-0-0-6
Remarks : Nil
* A: no. of lecture hours per week
B: no. of tutorial hours per week
C: no. of laboratory hours per week
D: no. of hours for projects, assignments, fieldwork etc per week
E: no. of hours for preparatory work by a student per week

Lecture Time Table
Class TypeWeek TypeWeek DayStartEndRoom

Tutorial Time Table
Attention: The tutorial timetables could be updated from time to time. Students are advised to check regularly for the latest update on the change of tutorial timing.
Class TypeWeek TypeWeek DayStartEndRoom Iteration
Available in Tutorial Balloting [Iteration 2].
Available in Tutorial Balloting [Iteration 2].
Available in Tutorial Balloting [Iteration 2].
Available in Tutorial Balloting [Iteration 2].
Available in Tutorial Balloting [Iteration 2].
Available in Tutorial Balloting [Iteration 2].

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