Restaurant revenue management through combinatorial auctions

Abstract

Booking a table in some popular restaurants, particularly in certain big cities, is becoming increasingly challenging. The number of requests to eat in those restaurants exceeds the available supply, resulting in a shortage of seating capacity. In recent years, the market for resale of restaurant reservations has emerged as possible solution to this problem. However, this practice does not offer to restaurateurs any protection on the certainty of booking, is unfair to customers, and can lead to a high no-show rate. This work presents an innovative framework for restaurant revenue management, which aims to optimise revenues by managing bookings at restaurants. Particularly, the concept of combinatorial auction is applied to allocate tables and menus to the customers who participate in the auction through a web platform. The winner determination problem is solved in order to assign requests to the bidding customers. Furthermore, a procedure to address the bid generation problem, based on realistic data, is also proposed. The scalability of the model is addressed with an extensive test phase. The applicability of this novel approach is also tested on a real Michelin-starred restaurant. Results of computational experiments suggest that the profitability of this practice has the potential to revolutionize the restaurant reservations sector in the near future.