A New Model for Smart and Sustainable Travel Using Mobile Tiny Houses: Optimizing Tourist Routes Across Cities

Abstract

This research presents a new sustainable tourism model using mobile tiny houses to optimize tourist routes across several cities in France. The proposed model integrates environmental, logistical, and experiential dimensions to minimize travel distance, maximize profit, and enhance the tourist experience. A mono-objective approach using Simulated Annealing (SA) was first implemented, followed by a multi-objective extension using Archived Multi-Objective Simulated Annealing (AMOSA) to balance economic cost and environmental impact. The model was tested on a realistic case study involving multiple French cities and monthly travel periods. Results showed that the optimized routes significantly reduced travel distance, minimized total cost, and supported carbon-friendly logistics. Tools such as Python, CPLEX, and GUROBI were used for implementation and validation.