Code for single-leg revenue management with fare-locking
This section includes code for single-leg revenue management with fare-locking. Clicking on the link in the title above downloads a zip file including the code. The code either sets up base test problems with a simple structure or randomly generates a large number of test problems. It includes an implementation of an approximate policy that is guaranteed to obtain at least half of the optimal total expected revenue and an implementation of a bid-price policy that uses bid-prices extracted from a linear programming formulation.
Network revenue management data sets
This section includes a number of network revenue management data sets together with the performances of different benchmark strategies on the problems.
Choice modeling data sets
This section includes a number of choice modeling data sets, where we randomly generate the subsets of products offered to customers and the products chosen by the customers out of the offered subsets. The choices of the customers are governed by a preference ranking based choice model. Clicking on the link in the title above downloads a zip file. The zip file includes the details of the preference ranking based choice model that drives the customer choices, along with Matlab code to fit a Markov chain choice model and a multinomial logit model to the data. The readme.txt files in the zip file explain the organization of the directories in the zip file.
Stochastic programming data sets
This section includes a number of two-stage stochastic programming data sets in in SMPS format.
Min-cost network flow and min-cost flow augmenting path packages
This section includes a Java implementation of min-cost network flow and min-cost flow augmenting path algorithms. NetworkTest.java includes an example that shows how to use the library.
If you use any of the material here, please include a reference to this webpage.