Proceedings of ICLT 2025
OPTIMIZING CROSS-BORDER SUSTAINABLE TOURISM ROUTES FOR ELECTRIC VEHICLES
Thachada Pluemjan; Direk Bowonsakulcharoen; Arunrat Sawettham
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. 153-158
Abstract
Purpose: Introduce a novel hybrid optimization model, combining genetic algorithms and simulated annealing, for designing efficient and sustainable cross-border electric vehicle tourism routes. Design/methodology/approach: Develop an optimization model that integrates a hybrid approach that combines Genetic Algorithms (GA) and Simulated Annealing (SA) to find the best tourism routes for electric vehicles, using a case study in Ubon Ratchathani province in Thailand and Champasak province in Laos. The chosen routes begin and end at Ubon Ratchathani Airport and pass through the Chong Mek – Vang Tao border checkpoint. Data were collected from official tourism websites, online travel platforms, and Google Maps. The performance of this hybrid method was subsequently evaluated against key metrics, demonstrating superior results in terms of travel time, energy consumption and tourist satisfaction. Findings: The study shows that the hybrid GA-SA method can effectively optimize cross-border tourism routes for electric vehicles that reduce travel time and distance while connecting important cultural and natural attractions. Compared to other planning methods, the hybrid approach offered better performance in terms of route efficiency and tourist satisfaction. Research limitations/implications: This study is limited to one case area and assumes constant travel conditions. It does not include real-time factors or user preferences. Practical implications: The model supports low-carbon route planning, EV infrastructure development, and sustainable tourism in cross-border regions. Originality/value: It supports sustainable tourism, enhances route efficiency, and expands the application of metaheuristic techniques in transportation and tourism planning, particularly in environmentally sensitive and regional development contexts.
Keywords
Cross-Border Tourism; Genetic Algorithms; Simulated Annealing; Electric Vehicles; Sustainable Tourism
Citation
Thachada Pluemjan; Direk Bowonsakulcharoen; Arunrat Sawettham (2025). OPTIMIZING CROSS-BORDER SUSTAINABLE TOURISM ROUTES FOR ELECTRIC VEHICLES. Proceedings of the International Conference on Logistics & Transport (ICLT 2025), Tokyo, Japan, pp. 153-158.