Constrained dynamic pricing for airport parking reservations

To make best use of technology on available big data (e.g., airport parking reservation data), we design and develop an innovative big data science solution for constrained dynamic pricing for airport parking reservations in the proposed research project undertaken by the intern. From scientific point of view, such a solution is novel in the sense that it will be capable of achieving multiple objectives (e.g., maximize revenue and other objectives) and solving the constrained dynamic pricing problem (in which price is constrained or bounded by some user-specified threshold). Moreover, it will be efficient in integrating big data from a wide variety of heterogeneous sources, as well as analyzing and learning data to make appropriate recommendation on prices. From the business/industrial point of view, such a solution will be beneficial to the partner organization by helping them to get an insight and better understanding of their data and enable it to further enhance its operation. To a further extent, the solution will be applicable and beneficial to other Canadian airports and/or parking facilities in other Canadian communities.

Faculty Supervisor:

Carson Leung


Deyu Deng


Winnipeg Airports Authority


Computer science


Transportation and warehousing


University of Manitoba



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