Managing restaurant tables using constraints

Restaurant table management can have significant impact on both profitability and the customer experience. The core of the issue is a complex dynamic combinatorial problem. We show how to model the problem as constraint satisfaction, with extensions which generate flexible seating plans and which maintain stability when changes occur. We describe an implemented system which provides advice to users in real time. The system is currently being evaluated in a restaurant environment.