Course Objective

    Linear programming is the fundamental form of the mathematical programming methodology. Central to the mathematical programming is the mathematical derivation, by which the properties and the algorithms of a mathematical optimization model were developed.

The course aims

• To understand the role of linear programming in engineering design and its importance.

• To introduce the significance of simplex theory and the concept of duality, decomposition etc.  in a linear programming problem.

• To improve the capability of logical reasoning and implementation of mathematical methods in a real problem.

Students Learning Outcomes (SLO)

Student having

• Improved reasoning skills and developing linear programming models to address social/economic/engineering problems.

• Improved knowledge on the practical application of linear programming.

• Improved knowledge on using techniques like simplex method, duality, decomposition etc. to solve problems.

• Improved ability to use mathematical methods in social/economics/ engineering problems.

• Improved decision-making skills, through optimizing objectives on an environment, having constrained resources.

Time and Venue

• Mondays 13:20-15:10  Wednesdays 13:20-14:10

               Classroom:

               Engineering Building I Room 102

Textbook

• Introduction to Linear Optimization,

Dimitris Bertsimas and John N. Tsitsiklis, Athena Scientific, 1997

• Linear Programming and Network Flows,

Mokhtar S. Bazaraa, John J. Jarvis, Hanif D. Sherali, Wiley, 4th Edition, 2009

Reference

• Large Scale Linear and Integer Optimization: A Unified Approach

Richard Kipp Martin, Springer, 1999

• Selected journal papers

Grading and Exams

• 3 Homework  15%  

• 3 Exams 48%

• 4 Labs 24%

• Individual project 13%

Attendance Policy 

• No more than 3 times of absences. You will not have the chance to have the final-score adjustment, i.e., bonus, at the end of the semester after 4 absences. (Official leaves, sick leaves, etc., require the official and doctor's proofs.) 

Explanation in Chinese: 全學期因「事假」或「未請假」而缺席未到的次數不超過3次的同學，期末結算成績時享有一併加總分 bonus 的「福利」。公假或病假...等等，屬於非事假的假別，不算在缺席次數中，唯須同學提供可資證明之照片或文件。

Note: For leave requests, please send an email to the professor and cc the TA 鄧雅之 

備註: 請假時請同時寄信給老師和助教鄧雅之

Note: When you are absent for 3 times, TA will send you a reminder about this.

備註: 當累積三次缺席,助教會發通告信提醒

• If you have no more than 3 times of absences, your final semester score won't be less than that of a "pass". This type of adjustment will be done for the whole group of students who are eligible to have the final-score adjustment, i.e., eligible to have bonus, without affecting the rank.

Explanation in Chinese:  「保底機制」: 全學期因「事假」或「未請假」而缺席未到的次數不超過3次的同學，學期總成績不低於「及格」。 「公平原則」: 因保底機制及前述加分福利所調分數，將確保維持這些符合調分資格同學的原始成績排名次序。

• No falsifying attendance (That is, penalty will be imposed when being marked present without actually attending class.) You will have 20 points deduction once found. 

Explanation in Chinese: 請只有真實出席的時候才點名簽到，「詐點」行為若發現，扣總分20。

    Homework/Project Policy 

• No plagiarism (That is, zero tolerance with more than three consecutive identical sentences.) You will receive 0 once found. 

Explanation in Chinese: 抄襲認定的標準是「連續三句話完全相同」，抄襲的作業及報告 0分計。 

  Study group Policy

• To enhance learning efficiency and effectiveness, each student must enroll in a study group. Please discuss as a group before each  homework due for at least 1 hour and take a photo. Attach the group photo in your homework submission and indicate the start and end time of the discussion. The discussion can be held online. The photo of an online study group discussion can be the screenshot of everyone's face. Please form a group with 4-5 students. If gathering everyone in the group, is infeasible, please "at least" find a pair to discuss and take photos of the pairs.

Explanation in Chinese: 交作業前請先與讀書會同學討論或核對答案，避免大方向錯誤或是粗心遺漏細節。如果沒辦法約到全組人，請每個人至少找到一個組員兩兩進行讀書會。

Group List 

    Integrity Policy

• Zero tolerance toward cheating. You will receive 0 once found.

Explanation in Chinese: 作弊「零」容忍 。

  AI tool Policy

• You can use AI as you wish unless there is an extra specification, yet you should check the correctness of the output. You are responsible to the errors it produces if not being corrected. 

Faculty

 Teaching Assistants