Developing Data Products Course Project

This App uses the R lpSolveAPI package within a Shinyapp to optimize airline revenue based on two inputs from the user:

• Demand for regular-priced seats
• Demand for discount-priced seats

The App then constructs a linear programming model (LP) using R code, solves the linear program with the lpSolveAPI package, and returns the objective value - the maximum revenue given the selected demand for the two inputs.

This App is hosted on an AWS Ubuntu server at the below link: Airline Revenue Optimization

The LP is formulated with two decision variables

• Number of regular-priced seats to sell
• Number of discount-priced seats to sell

The LP also has five constraints or inequalities

• Seats sold cannot exceed capacity of the plane (166 seats)
• Regular price seats sold cannot exceed regular demand
• Discount price seats sold cannot exceed discount demand
• Seats sold at both levels must be nonnegative

print(lprec)

Model name: 
                  reg  disc         
Maximize          617   238         
capacity            1     1  <=  166
reg_demand          1     0  <=  100
discount_demand     0     1  <=  150
reg_positive        1     0  >=    0
disc_positive       0     1  >=    0
Kind              Std   Std         
Type             Real  Real         
Upper             Inf   Inf         
Lower               0     0         

This problem is based on the lesson found here

MITx 15.071x The Analytics Edge

Airline Revenue Management

Information on the lpSolveAPI package can be found here

Package lpSolveAPI

lpSolveAPI Vignette