Proceedings of ICLT 2025
EFFICIENT ROUTE PLANNING FOR CONSERVATION TOURISM IN THE MEKONG: A HEURISTIC OPTIMIZATION APPROACH
Arunrat Sawettham; Padivarada Lomlai; Thachada Pluemjan; Supattraporn Saisomboon; Paweena Khampukka; Kraisak Yongkulwanich
Faculty of Management Science, Ubon Ratchathani University, Thailand; Faculty of Management Science, Ubon Ratchathani University, Thailand; Faculty of Management Science, Ubon Ratchathani University, Thailand; Faculty of Management Science, Ubon Ratchathani University, Thailand; Faculty of Management Science, Ubon Ratchathani University, Thailand; Faculty of Management Science, Ubon Ratchathani University, Thailand
International Conference on Logistics & Transport 2025, Tokyo, Japan, pp. 119-124
Abstract
Purpose: This study develops an efficient model for conservation tourism across 80 destinations in the Mekong region, spanning Thailand and the Lao People’s Democratic Republic (PDR). The research aims to novelty model Hybrid Decision Framework (HDF) integrates spatial optimization, pricing elasticity, and behavioral demand forecasting while promoting sustainable tourism practices. Design/methodology/approach: The study employs sustainability indicators by optimization techniques to identify the shortest routes, comparing their performance with the traditional approach. Location coordinates were collected within the study area, and the optimized routes were further enhanced by integrating dynamic pricing and AI-driven forecasting. Findings: The proposed method HDF significantly reduces travel distance compared to the TSP approach. Incorporating dynamic pricing and AI forecasting enables effective cost management and supports balanced distribution of tourist flows throughout the year, contributing to sustainable tourism in the Mekong region. Research limitations/implications (if applicable): This study focuses on a specific geographic area, which may limit the generalizability of the proposed model. Future research could expand the framework to larger regions and incorporate multimodal transport considerations. Practical implications (if applicable): The proposed route-planning model provides a practical tool for tourism planners and policymakers to improve conservation tourism efficiency, reduce operational costs, and promote environmentally responsible travel practices. Originality/value: This research introduces sustainability indicators an innovative integration of optimization techniques, dynamic pricing, and AI forecasting to support efficient and sustainable tourism route planning. It offers a replicable model for other conservation-focused tourism initiatives.
Keywords
Dynamic Pricing; Nearest Neighbour Heuristic (NNH); Local Search Optimization; Sustainable Travel; Traveling Salesman Problem (TSP)
Citation
Arunrat Sawettham; Padivarada Lomlai; Thachada Pluemjan; Supattraporn Saisomboon; Paweena Khampukka; Kraisak Yongkulwanich (2025). EFFICIENT ROUTE PLANNING FOR CONSERVATION TOURISM IN THE MEKONG: A HEURISTIC OPTIMIZATION APPROACH. Proceedings of the International Conference on Logistics & Transport (ICLT 2025), Tokyo, Japan, pp. 119-124.