| dc.description.abstract | The paper is addressing the significant issue of discontinuity of travel information and
free independent is faced with a complex of planning. There is the presence of travelers
who are approximated to constitute an estimated 80 percent of the tourists visiting
Sri Lanka. Although there are several local artificial intelligence systems that support
text, most do not offer customized, integrated, and safe itinerary generation, especially
in cases where they combine multi-modal transport and follow ethical principles.
To address these flaws, the proposed system is an intelligent web and mobile-based
system called TravelPlan. The unique hybrid architecture used by TravelPlan: the
user preferences are analyzed in the form of the machine learning models, and a
genetic algorithm is the central itinerary optimization engine. The most important
contribution is a stringent multi-criteria fitness function that streamlines the itinerary by
reducing the travelling time and cost as well as maximizing user interest, route efficiency,
and most importantly, a safety cultural weighting score developed by the company.
Methodology describes the process of putting fragmented transport, accommodation,
and point-of-interest information together into one geographic information object. A
comparison between the performance of the system and the performance of traditional
manual planning is provided through an evaluation plan using both technical metrics
including latency and budget adherence and the system usability scale to indicate that
TravelPlan will be able to foster efficient, responsible, and high-satisfaction independent
tourism in Sri Lanka | en_US |
