1963/1.206J16.77ESD215JThe Schedule design problem Outline Problem Definition and Objective Schedule design with Constant market Share Schedule design with variable market Share Schedule design solution Algorithm Results Next Steps A Look to the Future in airline schedule optimization

Outline Airline planning complexity Schedule disruptions Schedule dependability CDM Ground delay Program How do airlines recover the schedule? Traditional ARM; Model shortcomings Interdependency of passengers and aircraft operations

1.206J/16.77J/ESD.215J The Fleet Assignment Problem Outline Problem Definition and Objective Fleet Assignment Network Representation Fleet Assignment Model Fleet Assignment Solution Branch--bound-and- Results

1.206J/16.77J/ ESD. 215 Airline Schedule planning: multi-commodity Flows Outline Applications Problem definition Formulations Solutions Results

1.206J/16.77J/ESD.215J Airline Schedule Planning: Multi-commodity Flows Outline Applications Problem definition Formulations Solutions Computational results Integer multi-commodity network flow

Markov Decision Processes and Reinforcement Learning · Motivation earning policies through reinforcement Q values

Outline Objectives Agents and Their building Blocks Principles for building agents Modeling formalisms Algorithmic Principles Building an agent: The Mars Exploration rover

How Might a mouse search a Maze for Cheese? heese · State Space Search? As a Constraint Satisfaction Problem? Goal-directed Planning As a rule or production System? What is missing? Ideas in this lecture Objective is to accumulate rewards rather than goal states Task is to generate policies for how to act in all situations rather than a plan for a single starting situation

Probabilistic model Integrate over al!p(x1 Bel(x,)=ap(=;|x,)p(x1a1,=12a1-2,=0) ap(E, x )p(x, Ix, 1,a, p(|x,)p(x,1x1,a1)p(x1)d

Courtesy or Eric Feron and Sommer Gentry. Used with permission. Introduction to Linear Programming Eric Feron (updated Sommer Gentry)