Tourist Trip Design Problem with user preference and popularity: a case study of Langkawi Island / Nabilah Anuar Ahmad and Huda Zuhrah Ab. Halim

Langkawi Island received more than 1.8 million tourists in 2022 after the Malaysian Government introduced Langkawi Travel Bubble. This study aims to resolve the Tourist Trip Design Problem (TTDP) given user preference and popularity of Points of Interest (POIs). TTDP formulation falls under Orientee...

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Bibliographic Details
Main Authors: Anuar Ahmad, Nabilah, Ab. Halim, Huda Zuhrah
Format: Book Section
Language:English
Published: College of Computing, Informatics and Media, UiTM Perlis 2023
Subjects:
Online Access:https://ir.uitm.edu.my/id/eprint/100190/1/100190.pdf
https://ir.uitm.edu.my/id/eprint/100190/
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Summary:Langkawi Island received more than 1.8 million tourists in 2022 after the Malaysian Government introduced Langkawi Travel Bubble. This study aims to resolve the Tourist Trip Design Problem (TTDP) given user preference and popularity of Points of Interest (POIs). TTDP formulation falls under Orienteering Problem, which adopts the Integer Programming Formulation (Benjamin et al., 2019; Ruiz-Meza & Montoya-Torres, 2022). This study proposed enhancement in the greedy algorithm approach (Benjamin et al., 2019). A greedy algorithm solves a problem that selects the most appropriate option based on the current situation. Clarke Wright Saving Algorithm has been embedded in a greedy algorithm to find the shortest route between POIs selected by the algorithm, and it will create a sequence of POIs. The algorithm will choose POIs based on categories selected by the users. Users will choose three categories out of the six categories listed. The categories are; Forests, Island Adventure, Beaches and Waterfall, History and Culture, Shopping, and Fun. Then the algorithm will select POI if the cost of POI does not exceed the allocated budget. The algorithm also considers the popularity of POIs, operating hour, and touring time of POI. The carbon footprint is calculated for the best itinerary found.