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.;
2019-01-01

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.
978-1-7281-1481-1
978-1-7281-1482-8
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11386/4735105
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