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 nonlinear programming.  1  2.  solve problems of linear programming, integer programming and nonlinear programming with fundamental methods in optimization.  5  3.  apply linear programming tools to solve twoperson zerosum games.  2  4.  apply mathematical and computational methods of optimization in modeling formulating and solving reallife applicationsproblem  2  5.  the combination of CILOs 14  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.  15  39 hours in total  Learning through takehome assignments helps students understand techniques of basic methods in linear, integer and nonlinear programming as well as their applications in solving optimization problems.  14  afterclass  Learning through project(s) helps students apply mathematical and computational methods of optimization in formulating and solving more sophisticated reallife problems on linear/integer/nonlinear programming. It also helps students to communicate and collaborate effectively in the team.  34  afterclass  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  afterclass  Learning activities in Math Help Centre provides students extra help.  12, 4  afterclass 
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  12, 4  1530%  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.  Handin assignments  14  015%  These are skills based assessment to enable students to demonstrate techniques of applying optimization methods in a diversity of problems.  Project(s)  34  015%  Students are assessed on their ability in applying mathematical and computational methods to solve reallife 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 takehome assignments  14  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, Twoperson Zerosum Games, The Fundamental Theorem and Computational Techniques
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