Track 6
Revenue Management
Capacity-constrained pricing for perishable inventory: Littlewood's rule, EMSR booking limits, network RM, bid-price controls, overbooking, and competitive simulation.
Revenue Management Simulator
Pit FCFS, EMSR-b, bid-price, and dynamic pricing against each other in an airline market simulator. Watch bookings unfold in real time and compare revenue outcomes across hundreds of Monte Carlo replications.
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Topics
Pricing Scarce Inventory
Why capacity constraints push prices higher
See how capacity constraints push optimal prices above the unconstrained optimum, and learn why the shadow price of capacity is the bridge from static pricing to revenue management.
Filling Seats at the Right Price
Allocating capacity across fare classes
Observe an animated booking timeline filling fare classes, step through Littlewood's Rule, and see how nested allocation outperforms partitioned strategies.
Setting Booking Limits
EMSR heuristics and the spoilage-dilution tradeoff
Step through the EMSR-b algorithm, compare EMSR-a vs EMSR-b accuracy, and explore the spoilage-vs-dilution tradeoff at each booking limit.
How Many Extra Seats to Sell
Balancing empty seats against denied boardings
Run Monte Carlo simulations of show-up rates, and find the overbooking limit that maximizes expected net revenue after denied-boarding costs.
Managing a Route Network
Multi-leg itineraries and bid-price controls
Manage a small airline network: accept or reject booking requests across connecting itineraries, and compare manual decisions against LP-based bid prices.
Revenue Management Simulator
Comparing RM policies head-to-head
Pit FCFS, EMSR-b, bid-price, and dynamic pricing against each other in an airline market simulator. Watch bookings unfold in real time and compare revenue outcomes across hundreds of Monte Carlo replications.