15.066J 制造与运营系统优化分析

MIT Course 15 · Operations Research/Statistics · 课号 15.066J

TL;DR

• 系统级制造与服务运营优化，以排队论、库存控制理论与生产能力规划为核心工具。
• 利特尔法则（Little's Law）与马尔可夫排队网络量化在制品库存与客户等待时间。
• 报童模型与动态安全库存策略平衡服务水平与缺货/积压风险成本。

课程简介 / Description

One objective of 15.066J is to introduce modeling, optimization and simulation, as it applies to the study and analysis of manufacturing systems for decision support. The introduction of optimization models and algorithms provide a framework to think about a wide range of issues that arise in manufacturing systems. The second objective is to expose students to a wide range of applications for these methods and models, and to integrate this material with their introduction to operations management.

讲义 / Lecture Notes

• 1
• 1
  • Introduction and Overview (PDF)
• 2
  • LP (Linear Programming) - Introduction, Formulations and Geometry (PDF)
• 3
  • LP (Linear Programming) - Example (PDF)
• 2
• 4
  • Networks - Introduction (PDF)
• 5
  • LP (Linear Programming) - Example (PDF)
• 3
• 6
  • LP (Linear Programming) - Example: Tony Palumbo, Ford
• 7
  • LP (Linear Programming) - Solution Methods and Sensitivity Analysis (PDF)
• 4
• 8
  • Integer Programming - Formulations (PDF)
• 9
  • Integer Programming - Algorithms (PDF)
• 10
  • Integer Programming - Heuristics
• 5
• 11
  • Debriefing of Inventory Simulation (with
  • 15.761
  • )
• 12
  • Stochastic LP (Linear Programming)
• 13
  • Optimization in Practice: John Bean, Intel
• 6
• 14
  • Introduction, Simulation Process and Stochastic Modeling (PDF)
• 15
  • Monte-Carlo Theory and Examples (with Crystal Ball®) (PDF)
• 7
• 16
  • Ontario Gateway Case Discussion (PDF)
• 17
  • Discrete-Event Framework and Examples (with SIMUL8®)
• 18
  • Theory of Constraints (Joint Session with
  • 15.761
  • )
• 8
• 19
  • Discrete Event Case Discussion
• 20
  • Experimental Design and Simulation Analysis (PDF)
• 21
  • Advanced Modeling, Simulation-Based Optimization (PDF)
• 9
• 22
  • Non Linear Programming - Formulations (PDF)
• 23
  • NLP (Non Linear Programming) - Examples and Algorithms (PDF)
  • Langrangean Example (PDF)
• 10
• 24
  • Project Presentations
• 25
  • Project Presentations
• 26
  • Project Presentations and Class Summary (PDF)

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