lec10 schedule design 2003

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1.206J/16.77J/ESD.215J Airline Schedule Planning : 

1.206J/16.77J/ESD.215J Airline Schedule Planning Cynthia Barnhart Spring 2003

1.963/1.206J/16.77J/ESD.215J The Schedule Design Problem: 

1.963/1.206J/16.77J/ESD.215J The 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

Airline Schedule Planning: 

Assign aircraft types to flight legs such that contribution is maximized Airline Schedule Planning Schedule Design Select optimal set of flight legs in a schedule

Objectives: 

Objectives Given origin-destination demands and fares, fleet composition and size, fleet operating characteristics and costs Find the revenue maximizing flight schedule

Schedule Design: Fixed Flight Network, Flexible Schedule Approach: 

Schedule Design: Fixed Flight Network, Flexible Schedule Approach Fleet assignment model with time windows Allows flights to be re-timed slightly (plus/ minus 10 minutes) to allow for improved utilization of aircraft and improved capacity assignments Initial step in integrating flight schedule design and fleet assignment decisions

Schedule Design: Optional Flights, Flexible Schedule Approach: 

Schedule Design: Optional Flights, Flexible Schedule Approach Fleet assignment with “optional” flight legs Additional flight legs representing varying flight departure times Additional flight legs representing new flights Option to eliminate existing flights from future flight network Incremental Schedule Design

Integrated, Incremental Schedule Design and Fleet Assignment Models: 

Integrated, Incremental Schedule Design and Fleet Assignment Models Addition Candidates Base Schedule Select optimal set of flight legs from master flight list Assign fleet types to flight legs

Demand and Supply Interactions: 

Demand and Supply Interactions

Schedule Design: Constant Market Share Model: 

Schedule Design: Constant Market Share Model Constant market share model Integrated Schedule Design and Fleet Assignment Model (ISD-FAM) Utilize recapture mechanism to adjust demand approximately

ISD-FAM: Example: 

ISD-FAM: Example

ISD-FAM Formulation: 

ISD-FAM Formulation

ISD-FAM Formulation: 

ISD-FAM Formulation Flight Selection

ISD-FAM Formulation: 

ISD-FAM Formulation Flight Selection

Schedule Design: Variable Market Share Model: 

Schedule Design: Variable Market Share Model Variable market share model Extended Schedule Design and Fleet Assignment Model (ESD-FAM) Utilize demand correction term to adjust demand explicitly

ESD-FAM: Demand Correction: 

ESD-FAM: Demand Correction -30 2nd degree correction Data Quality Issue

ESD-FAM Formulation: 

ESD-FAM Formulation

ESD-FAM Formulation: 

ESD-FAM Formulation

ESD-FAM Formulation: 

ESD-FAM Formulation

Solution Algorithm: 

Solution Algorithm START

State Of The Practice/ Theory: 

State Of The Practice/ Theory Practice: Most schedule decisions made without optimization At least one major airline uses Fleet Assignment with Time Windows Implementation of Incremental Schedule Design approach underway at a major airline Theory: Models and algorithms for incremental schedule design have been developed and prototyped Validation in progress

Computational Experiences: 

Computational Experiences ISD-FAM requires long runtimes and large amounts of memory ~ 40 minutes on a workstation class computer for medium size (800 legs) schedules ~ 20 hours on a 6-processor workstation, running parallel CPLEX for full size (2,000 legs) schedules ESD-FAM takes even longer runtimes and exhausts the memory in some cases 40 mins (ISD-FAM) vs. 12 hrs (ESD-FAM) on same medium size schedule

Schedule Design: Results: 

Schedule Design: Results Demand and supply interactions ESD-FAM captures interactions more accurately Resulting schedules operate fewer flights Lower operating costs Fewer aircraft required ~$100 - $350 million improvement annually Compared to planners’ schedules Exclude benefits from saved aircraft

Schedule Design Results: 

Schedule Design Results Results are subject to several caveats Plans are often disrupted Competitors’ responses Underlying assumptions Deterministic demand Optimal control of passengers Demand forecast Recapture rates/Demand correction terms Nonetheless, significant improvements are achievable

Potential for Improved Results: 

Potential for Improved Results Replace IFAM with SFAM 1

SFAM Basic Concept: 

SFAM Basic Concept Isolate network effects Spill occurs only on constrained legs

A Look to the Future: Airline Schedule Planning Integration: 

A Look to the Future: Airline Schedule Planning Integration Schedule Design Fleet Assignment Fleet Assignment Aircraft Routing Aircraft Routing Crew Scheduling Fleet Assignment Crew Scheduling Integrating crew scheduling and fleet assignment models yields: Additional 3% savings in total operating, spill and crew costs Fleeting costs increase by about 1% Crew costs decrease by about 7%

A Look to the Future: Real-time Decision Making: 

A Look to the Future: Real-time Decision Making For a typical airline, about 10% of scheduled revenue flights are affected by irregularities (like inclement weather, maintenance problems, etc.) According to the New York Times, irregular operations (due mostly to weather) result in more than $440 million per year in lost revenue, crew overtime pay, and passenger hospitality costs Increasing use and acceptance of optimization-based decision support tools for operations recovery

A Look to the Future: Robust Scheduling: 

A Look to the Future: Robust Scheduling Issue: Optimizing “plans” results in minimized planned costs, not realized costs Optimized plans have little slack, resulting in Increased likelihood of plan “breakage” during operations Fewer recovery options Challenge: Building “robust” plans that achieve minimal realized costs