Course Objective

    Linear programming is the fundamental form of the mathematical programming methodology. Central to the mathematical programming is the modling thinking and the logical derivation. The course aims to

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

• Introduce the significance of polyhedron theory, simplex method and the concept of duality, decomposition etc.  in a linear programming problem.

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

Students Learning Outcomes ("core abilities")

Students are expected to have 

• 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 202

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%                    

• 2 Paper-based exams 32%

• 1 Oral exam (with drawn question) 16%

• 4 In-class activities 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.

備註: 請假時請同時寄信給老師和負責助教, 但不必要使用請假系統

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。 

• Please specify how the AI is used. Indicate the process of using AI in generting answers or modifying answers.

Explaination in Chinese: 作業繳交文檔中需要描述自己在準備該次作業的過程中, AI 是如何被使用.務必如實標記具體使用AI的流程步驟. 如果完全沒有使用AI則標記 「完全沒有使用 AI」. 

    Integrity Policy

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

Explanation in Chinese: 作弊「零」容忍 。

  AI tool Policy

• You should specify clearly how the AI is used for preparing homework submission or project repoert so the entire process of your work can be reproduced. If not using AI, please specify 100% human-written. 

• Use AI to support, not substitute. Make sure the "core ability" stay yours. That is, make sure you can 

  • brainstorm and think about the problems as a trained graduate student            

  • answer technical questions orally without AI's assistance

  • commute and share with students and experts in this domain

  • verify the correctness and spot the errors from a written text

Faculty

 Teaching Assistants