Skip to content

Castle Labs

ComputAtional STochastic optimization and LEarning

  • Home
  • Papers
    • What’s new?
    • General Introductions
      • Books
      • Surveys/Reviews/Book Chapters
    • General Purpose Methods
      • Optimal Learning
      • Approximate Dynamic Programming
      • Machine Learning
      • Stochastic Optimization
      • Deterministic Optimization
      • Queuing Theory
    • Models and Algorithms for General Resource Allocation Problems
      • Modeling and Problem Representation
      • General Dynamic Resource Management
      • Multiagent Control
    • Applications
      • Energy Systems Analysis
      • Dynamic Fleet Management (Trucking, Rail, Air)
      • Military Airlift
      • Health and Medical Applications
      • Vehicle Routing and Scheduling Problems
      • Service Network Design
      • Machine Scheduling
      • Physical Distribution
      • Traffic and Public Transportation
      • Freight Demand Estimation
    • General Interest
  • Presentations
  • Impact on Industry
  • Timeline of Developments
  • People
  • Courses
  • Datasets
  • Software
  • Awards
  • Corporate Partners

©Warren B. Powell, 1997 – 2017.

Princeton University

General Introductions

  • Books
  • Surveys/reviews/book chapters
  • Clearing the jungle of stochastic optimization (a series of tutorials)

© Warren B. Powell, 1997 - 2017. All rights reserved. powell@princeton.edu