此網頁為台灣大學資訊管理學系「作業研究應用與實作」的課程網頁。 以統計方法與最佳化理論為基礎，深入探討各種作業研究模型於實務應用問題，包含產能規劃、供應鏈管理、績效評估、背包問題、設施規劃、投資組合、保險醫療等。 This course will provide students to learn the methodologies of operations research and its applications to the real problem. The models include deterministic models (such as linear programming, multi-criteria decision analysis, data envelopment analysis, etc.) and stochastic models (such as Bayesian decision analysis, stochastic programming, Markov decision process, etc.). The course integrates the knowledge domains of the management and engineering, applied in capacity planning, facility layout, supply chain, manufacturing scheduling, performance evaluation, vendor selection and order allocation, Bin-packing, financial investment, etc. We develop the implementation capability of the information system in practice. Finally we should know how to solve the real problem systematically using optimization or statistical methods.

授課老師為李家岩老師

1. Python+Gurobi / Python+Pulp

1. 漸進抽樣法pdf(Approximation and Sampling Method)
2. 漸進抽樣法code(Approximation and Sampling Method)

1. 動態供應鏈(Dynamic Supply Chain Management)

1. MODA: Prior Articulation of Preference- Compromise Programming
2. MODA: Progressive Articulation of Preferences- The Step Method(STEM)
3. 投資組合最佳化(Investment Portfolio Optimization)
4. 廠商評選與訂單配置(Vendor Selection and Order Allocation)

1. 數據包絡分析概論(Introduction to Data Envelopment Analysis)
2. 數據包絡分析(Data Envelopment Analysis)
3. 網路數據包絡分析(Network Data Envelopment Analysis)
4. 隨機無母數數據包絡(Stochastic Nonparametric Envelopment of Data, StoNED)

1. 馬可夫決策過程(Markov Decision Process)
2. 強化學習概論(Introduction to Reinforcement Learning)
3. 深度強化學習概論(Introduction to Deep Reinforcement Learning)
4. 多目標強化學習(Multi-Objective Reinforement Learning)
5. 強化學習於生產排程1(Reinforcement Learning for Flow Shop Scheduling
6. 強化學習於生產排程2(Reinforcement Learning for Semiconductor Scheduling)

1. 數學規劃 Mathematical Programming for Job Shop Scheduling
2. 數學規劃 Mathematical Programming for Flexible Job Shop
3. 基因演算法於生產排程1(Genetic Algorithm for Job Shop Scheduling-1)
4. 基因演算法於生產排程2(Genetic Algorithm for Job Shop Scheduling-2)
5. Nondominated Sorting Genetic Algorithm II (NSGA-II for Job Shop Scheduling)

1. 禁忌搜尋法(Tabu Search Algorithm)
2. 模擬退火法(Simulated Annealing Algorithm)
3. 基因演算法(Genetic Algorithm)