Stochastic programming for multiple-leg network revenue management

Airline seat inventory control is a very profitable tool in the airline industry. Mathematical programming models provide booking limits or bid-prices for all itineraries and fare classes based on demand forecasts. But the actual revenue generated in the booking process fails to meet expectations. Simple deterministic models based on expected demand generate better revenue than more advanced probabilistic models. Recently suggested models put even more effort into demand forecasting. We will show that the dynamic booking process rather than the demand forecasts needs to be addressed. In particular the nesting strategies applied in booking control will counter-effect the profitability of advanced estimation of booking limits and bid-prices.simulation;revenue management;mathematical programming

Models and techniques for hotel revenue management using a rolling horizon.

This paper studies decision rules for accepting reservations for stays in a hotel based on deterministic and stochastic mathematical programming techniques. Booking control strategies are constructed that include ideas for nesting, booking limits and bid prices. We allow for multiple day stays. Instead of optimizing a decision period consisting of a fixed set of target booking days, we simultaneously optimize the complete range of target booking dates that are open for booking at the moment of optimization. This yields a rolling horizon of overlapping decision periods, which will conveniently capture the effects of overlapping stays.Revenue management;Mathematical programming;Yield management

Models and Techniques for Hotel Revenue Management Using a Roling Horizon

AbstractThis paper studies decision rules for accepting reservations for stays in a hotel based on deterministic and stochastic mathematical programming techniques. Booking control strategies are constructed that include ideas for nesting, booking limits and bid prices. We allow for multiple day stays. Instead of optimizing a decision period consisting of a fixed set of target booking days, we simultaneously optimize the complete range of target booking dates that are open for booking at the moment of optimization. This yields a rolling horizon of overlapping decision periods, which will conveniently capture the effects of overlapping stays.mathematical programming;Revenue Management;yield management

Rostering at a Dutch Security Firm

The roster planning process at the Dutch security firm NVD was traditionally carried out by hand. A few years NVD was traditionally carried out by hand. A few years ago, because of changing labor laws in the Netherlands, this became practically impossible. We developed a decision support system which has four main modules. The first one checks given rosters for feasibility with respect to the complicated rules of the current Collective Labor Agreement. A second module generates feasible rosters. The third one evaluates each roster with respect to its cost and ergonomic criteria. Finally, the fourth module uses mathematical programming based methods to select high quality rosters. The DSS has received rave reviews from upper management, security employees as well as the planners, who have gained enormous insight into the planning process. The DSS is currently being implemented and will be operational within the near future.decision support systems;information systems;labor;applications;integer;programming;search and surveillance

Models and techniques for hotel revenue management using a rolling horizon.

This paper studies decision rules for accepting reservations for stays in a hotel based on deterministic and stochastic mathematical programming techniques. Booking control strategies are constructed that include ideas for nesting, booking limits and bid prices. We allow for multiple day stays. Instead of optimizing a decision period consisting of a fixed set of target booking days, we simultaneously optimize the complete range of target booking dates that are open for booking at the moment of optimization. This yields a rolling horizon of overlapping decision periods, which will conveniently capture the effects of overlapping stays

Stochastic programming for multiple-leg network revenue management

Airline seat inventory control is a very profitable tool in the airline industry. Mathematical programming models provide booking limits or bid-prices for all itineraries and fare classes based on demand forecasts. But the actual revenue generated in the booking process fails to meet expectations. Simple deterministic models based on expected demand generate better revenue than more advanced probabilistic models. Recently suggested models put even more effort into demand forecasting. We will show that the dynamic booking process rather than the demand forecasts needs to be addressed. In particular the nesting strategies applied in booking control will counter-effect the profitability of advanced estimation of booking limits and bid-prices

Rostering at a Dutch Security Firm

The roster planning process at the Dutch security firm NVD was traditionally carried out by hand. A few year