校際選修

115-1 選課時程

進行中

  • 初選第一階段 6/15/2026
  • 初選第二階段 6/22/2026
  • 校際選修 8/24/2026
  • 初選第三階段 8/31/2026
  • 開學後加退選 9/7/2026
  • 逾期加退選 9/21/2026
選課資源

作業研究(二)

Operations Research (II)

學期
114-2
學分
3 學分
當期課號
517012
永久課號
MGCM10003
開課單位
管理學院共同課程
授課教師
洪暉智
校區
光復
類別
必修
上課時間表
週二
2
09:00–09:50
作業研究(二)
MB520
3 節連堂
3
10:10–11:00
4
11:10–12:00

* 根據陽明交大上課時間表所列

概述

This is the second course that introduces deterministic and probabilistic optimization models such as dynamic programming, integer programming, nonlinear programming, Markov chain and queueing theory. This course focuses on modeling approaches, fundamental solution methodologies and their applications to the real world.

先修科目

Calculus and Probability Theory

教學方式

演習課教學助理每週舉行課程及作業講解,學生可自由參加。(The homework assignments will be lectured by our Teaching Assistant weekly and students' participation is optional.) 相關教學資料提供於教學平台。 (Relevant teaching materials are provided on the Virtual Learning Environment.) https://e3.nycu.edu.tw *** 詳情請至 [教材列表] 下載課程綱要。

評分方式

學期作業、考試、評量 (Homework, Examination, and Grading): 成績評量方法 (Grading): (a) 二次共同考試 (Two Common Examinations):Total 70% (35% for each exam). (b) 平時成績 (Individual Homework Assignments, Attendance, and Others): Total 30% *** 考試時間、詳情平時成績分配方法,請至 [教材列表] 下載課程綱要。

課程大綱
  • DTMC, CTMC, and Queueing Theory
  • Integer Programming and Discrete Optimization
  • Non-linear Programming
  • Stochastic Process and Markov Chain
週次計畫
週次主題
第 1 週28.1 Stochastic Processes 28.2 Markov Chains
第 2 週28.3 Chapman-Kolmogorov Equations 28.4 Classification of States of a Markov Chain
第 3 週28.5 Long-Run Properties of Markov Chain
第 4 週28.6 First Passage Times 28.7 Absorbing States
第 5 週17.1 Prototype Example 17.2 Basic Structure of Queueing Models 17.3 Examples of Real Queueing Systems 17.4 The Role of the Exponential Distribution
第 6 週17.5 The Birth-and-Death Process 17.6 Queueing Models Based on the Birth-and-Death Process
第 7 週17.9 Queueing Networks 12.1 Prototype Example 12.2 Some BIP Applications
第 8 週Midterm Exam (35%)
第 9 週12.3 Innovative Uses of Binary Variables in Model Formulation 12.4 Some Formulation Examples 12.5 Some Perspectives on Solving Integer Programming Problem
第 10 週12.6 The Branch-and-Bound Technique and its Application to Binary integer Programming 12.7 A Branch-and-Bounds Algorithm for the Mixed Integer Programming
第 11 週13.1 Sample applications 13.2 Graphical Illustration of Nonlinear Programming Problems
第 12 週13.3 Types of Nonlinear Programming Problems 13.4 One-Variable Unconstrained Optimization
第 13 週13.5 Multivariable Unconstrained Optimization
第 14 週13.6 The Karush-Kuhn-Tucker(KKT) Conditions for Constrained Optimization
第 15 週13.7 Quadratic Programming
第 16 週Final Exam (35%)
教科書

Frederick S. Hillier and Gerald J. Lieberman, Introduction to Operations Research, 11th Edition, McGraw-Hill, 2021.

Office Hours
地點
各授課教師另行公布 (To Be Announced)
時間
各授課教師另行公布 (To Be Announced)
聯絡方式
各授課教師另行公布 (To Be Announced)