MA3515 Introduction to Optimization

Part I

Course Duration: One Semester
Credit Units: 3
Level: B3
Medium of Instruction: English
Prerequisites: MA2503 
Precursors: Nil
Equivalent Courses: Nil
Exclusive Courses: Nil

Part II      

Course Aims:
This course introduces basic concepts and methods of optimization. It emphasizes equally all three aspects of understanding, algorithms and applications. It also equips students with computing techniques and ability of applying taught methods to solve practical problems.

Course Intended Learning Outcomes (CILOs)
Upon successful completion of this course, students should be able to:

No.

CILOs                    

Weighting
(if applicable)

1.

explain clearly basic concepts of linear and non-linear programming.

1

2.

solve problems of linear programming, integer programming and non-linear programming with fundamental methods in optimization.

5

3.

apply linear programming tools to solve two-person zero-sum games.

2

4.

apply mathematical and computational methods of optimization in modeling formulating and solving real-life applicationsproblem

2

5.

the combination of CILOs 1-4

3

Teaching and learning Activities (TLAs)
Indicative of likely activities and tasks students will undertake to learn in this course. Final details will be provided to students in their first week of attendance in this course.

TLAs

CILO No.

Hours/week

Learning through teaching is primarily based on lectures.

1--5

39 hours in total

Learning through take-home assignments helps students understand techniques of basic methods in linear, integer and non-linear programming as well as their applications in solving optimization problems.

1--4

after-class

Learning through project(s) helps students apply mathematical and computational methods of optimization in formulating and solving more sophisticated real-life problems on linear/integer/non-linear programming. It also helps students to communicate and collaborate effectively in the team.

3--4

after-class

Learning through online examples for applications helps students create and sormulate mathematical models and apply to a range of practical problems in economics/science.

4

after-class

Learning activities in Math Help Centre provides students extra help.

1--2, 4

after-class

Assessment Tasks/Activities
(designed to assess how well the students achieve the CILOs)

30% Coursework
70% Examination (Duration: 3 hours, at the end of the semester)

For a student to pass the course, at least 30% of the maximum mark for the examination must be obtained.

Assessment Tasks/Activities

CILO No.

Weighting
(if applicable)

Remarks

Test

 

1--2, 4

15-30%

Questions are designed for the part of the course to see how well the students have learned basic concepts of methods in linear programming and recognized their applications in solving optimization problems.

Hand-in assignments

1--4

0-15%

These are skills based assessment to enable students to demonstrate techniques of applying optimization methods in a diversity of problems.

Project(s)

3--4

0-15%

Students are assessed on their ability in applying mathematical and computational methods to solve real-life optimization problems, as well as on the presentation of solutions with analysis.

Examination

5

70%

Examination questions are designed to see how far students have achieved their intended learning outcomes. Questions will primarily be skills and understanding based to assess the student’s versatility in basic methods of mathematical programming.

Formative take-home assignments

1--4

0%

The assignments provide students chances to demonstrate their achievements on techniques of optimization learned in this course.

Grading of Student Achievement: Refer to Grading of Courses in the Academic Regulations

Part III     

Keyword Syllabus:
Examples of Optimization Problems. Simplex Method for Linear Programming Problems. Duality Theory of Linear Optimization. Sensitivity Analysis for Linear Programming Problems, Cutting Plane Methods for Integer Programming Problems, Two-person Zero-sum Games, The Fundamental Theorem and Computational Techniques

 

 

 

Related Links
Department of Mathematics