We consider the Cruise Itinerary Schedule Design (CISD) problem, which consists in identifying a cruise itinerary in order to optimize the payoff of a cruising company. To deal with this problem we present an optimization strategy based on a parameters optimization process. We exploits the Simulation exploration and Optimization Framework for the cloud (SOF) for building our computing intensive process on a cloud computing infrastructure. The optimization process is based on a heuristic tabu-search strategy, which computes and evaluates the cruise schedule and a genetic algorithm that optimizes the parameters of the heuristic search. We have evaluated the proposed solution in terms of quality as well as the scalability/cost efficiency on the cloud infrastructure Amazon Web Services.
Large-scale Optimized Searching for Cruise Itinerary Scheduling on the Cloud
Carillo M.;D'Auria M.;Serrapica F.;Spagnuolo C.;
2019
Abstract
We consider the Cruise Itinerary Schedule Design (CISD) problem, which consists in identifying a cruise itinerary in order to optimize the payoff of a cruising company. To deal with this problem we present an optimization strategy based on a parameters optimization process. We exploits the Simulation exploration and Optimization Framework for the cloud (SOF) for building our computing intensive process on a cloud computing infrastructure. The optimization process is based on a heuristic tabu-search strategy, which computes and evaluates the cruise schedule and a genetic algorithm that optimizes the parameters of the heuristic search. We have evaluated the proposed solution in terms of quality as well as the scalability/cost efficiency on the cloud infrastructure Amazon Web Services.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
