Cruise onboard itinerary planning for multi passengers with service venue capacity and time-window constraints

Abstract

The design of personalized onboard itineraries for multiple cruise passengers plays an important role in improving the tourism experience on cruise. Different from itinerary planning for city traveling, the venues on cruise suffer from strict capacity and time-window constraints due to the safety requirements, which results in the coupling effects between itineraries of multiple passengers. This study constructs an optimization model to balancing the gap between passengers while maximizing passenger benefits, develops an Adaptive Large Neighborhood Search algorithm based on Improved destruction-repair operators (IOALNS) to solve multi-passenger itinerary planning. Extensive analyses are performed to demonstrate the performance advantages of the IOALNS algorithm in solving instances with varying sizes. Finally, the test results of cruise passenger instances show that compared with existing multi-passenger travel planning algorithms, the proposed algorithm can improve passenger efficiency by at least 9.98% and reduce computation time by more than 50%. These effectively improve passenger satisfaction and operational efficiency in the cruise industry.