Detection of local tourism systems by threshold accepting

Despite the importance of tourism as a leading industry in the development of a country's economy, there is a lack of criteria and methodologies for the detection, promotion, and governance of local tourism systems. We propose a quantitative approach for the detection of local tourism systems the size of which is optimal with respect to geographical, economic, and demographical criteria: we formulate the problem as an optimization problem and we solve it by a metaheuristic approach; then we compare the obtained results with standard clustering approaches and with an exact optimization solver. Results show that our approach requires low computational times to provide results that are better than other clustering techniques and than the current approach used by local authorities.

Despite the importance of tourism as a leading industry in the development of a country's economy, there is a lack of criteria and methodologies for the detection, promotion, and governance of local tourism systems. We propose a quantitative approach for the detection of local tourism systems the size of which is optimal with respect to geographical, economic, and demographical criteria: we formulate the problem as an optimisation problem and we solve it by a metaheuristic approach; then we compare the obtained results with standard clustering approaches and with an exact optimisation solver. Results show that our approach requires low computational times to provide results that are better than other clustering techniques and than the current approach used by local authorities.