基本素養 Basic Literacy

注重人性的尊嚴、價值與培養自信心
The aim is to emphasize dignity and values of humanity, and cultivate self-confidence.
具備法治觀念與培養尊重及包容的工作態度與倫理
The aim is to learn rules of law education and develop working manner and ethics with honor and tolerance.
熱愛生命,關懷弱勢
The aim is to learn to adore life and to show care for the vulnerable.
培養外語能力並積極參與國際學術活動
The aim is to acquire knowledge and develop capabilities in learning foreign languages and aggressively joining international academic activities.

核心能力 Competence

具備製造資訊與系統領域相關知識之能力。
The aim is to acquire knowledge and develop capabilities in manufacturing information and systems.
具備E化製造領域相關知識之能力
The aim is to acquire knowledge and developing capabilities in e-Manufacturing infrastructure.
資訊技術導入工業自動化相關領與能力
The aim is to apply Information and System technology into industry for improving the efficiency and performance of manufacturing technology.
具備獨立思考、分析判斷與解決製造資訊與系統領域問題之能力
The aim is to acquire knowledge and develop capabilities of independently thinking, analyzing, and solving problems in manufacturing information and systems.
具備研究結果分析與判斷之能力
The aim is to acquire knowledge to analize research results.
具備跨領域有效溝通表達的專業語文能力
The aim is to acquire knowledge of efficient communications for crossing research area through professional language expression.
具備研讀及撰寫專業論文之能力
The aim is to acquire knowledge of reading and writing professional papers.
具備組織與領導團隊及從事創新設計之能力
The aim is to acquire knowledge of leadership for team working and innovative design.
具備凝聚團隊精神、創新製造資訊與系統領域實務所需之技術及系統整合溝通之能力
The aim is to acquire knowledge and develop capabilities of solidifying team-working spirit, and acquire knowledge of practical techniques and communication for system integration in the innovative manufacturing information and systems.

課程概述 Course Description

本課程將使學生了解作業研究方法在製造與資訊系統上之應用,評估製造與服務系統績效以及最佳化產能規劃與配置,進而改善生產力並提升決策品質。分析模型包含了確定性模式(線性規劃、多準則決策分析、賽局理論等)與隨機性模式(統計決策理論、隨機規劃、馬可夫決策過程等),結合工程與管理領域的相關知識,應用於供應鏈、網路最佳化、醫療疾病篩檢、維修可靠度、製造排程、績效評估、選商與訂單配置、庫存控制等,透過工廠參訪與實作練習,藉由統計與最佳化的方法有系統地建模以解決實務問題。
This course will provide students to learn the methodologies of operations research applied in manufacturing and information systems. We evaluate the performance of manufacturing and service systems and optimize capacity planning and allocation for improving productivity and decision quality. The models include deterministic models (such as linear programming, multi-criteria decision analysis, game theory, etc.) and stochastic models (such as statistical decision theory, stochastic programming, Markov decision process, etc.). The course integrates the knowledge domains of the engineering and management, applied in supply chain, network optimization, health-care and preventive medicine, maintenance reliability, manufacturing scheduling, performance evaluation, vendor selection and order allocation, inventory control, etc. We join the business visits and field survey, and develop the ability of implementation in practice. Finally we should know how to solve the real problem systematically using statistics or optimization methods.

課程學習目標 Course Objectives

  • Know the advanced techniques of operations research
  • Create theoretical model to solve the problem in real setting
  • System development and implementation
  • 課程進度 Progress Description

    進度說明 Progress Description
    1Review of Linear Programming and Markov Chain (線性規劃與馬可夫鏈)
    2SP: Stochastic Programming with Two-stage Recourse Problem (隨機規劃)
    3SP: The Value of Information and the Stochastic Solution (資訊價值)
    4SP: Approximation and Sampling Methods (漸進與抽樣隨機規劃)
    5Capacity Planning and Scheduling Optimization (產能規畫與生產排程最佳化)
    6Facility Layout and Goal Programming (設施規劃與目標規劃)
    7Bin-packing Problem (Three-dimensional Knapsack Problem) and Piece-wise Linearization (貨櫃裝載三維度背包問題與分段線性化)
    8Dynamic Supply Chain Optimization and Conjunctive Constraints (動態供應鏈與連結限制式)
    9Specialist Lecture (專家演講與教學: 作業研究與實證)
    10Multi-Objective Decision Analysis and Investment Portfolio Optimization (多目標規劃與投資組合最佳化)
    11MDP: Markov Decision Processes I (馬可夫決策過程)
    12MDP: Markov Decision Processes II (馬可夫決策過程)
    13RL: Reinforcement Learning I (強化學習)
    14RL: Reinforcement Learning II (強化學習)
    15Team Project Discussion (分組實作討論)
    16Team Project Discussion (分組實作討論)
    17Team Project Discussion (分組實作討論)
    18Final Presentation
     以上每週進度教師可依上課情況做適度調整。The schedule may be subject to change.

    有關課程其他調查 Other Surveys of Courses

    1.本課程是否規劃業界教師參與教學或演講?
    Is there any industry specialist invited in this course? How many times?
    2.本課程是否規劃含校外實習(並非參訪)?
    Are there any internships involved in the course? How many hours?
    3.本課程是否可歸認為學術倫理課程?
    Is this course recognized as an academic ethics course? In the course how many hours are regarding academic ethics topics?
    4.本課程是否屬進入社區實踐課程?
    Is this course recognized as a Community engagement and Service learning course? Which community will be engaged?