Article: Smart tourism decision support system based on dual-heuristic algorithms Journal: International Journal of Information and Communication Technology (IJICT) 2026 Vol.27 No.37 pp.66 - 88 Abstract: This study proposes an innovative tourism decision-support system driven by a dual-heuristic algorithm to overcome the subjectivity and low adaptability of traditional methods. The system integrates the analytic hierarchy process and an improved genetic algorithm to construct a scenic spot evaluation model. At the same time, a particle swarm optimisation algorithm enhances a back-propagation neural network for visitor flow prediction. Experiments show the model achieves losses of 0.026 and 0.023, with evaluation accuracies up to 92.47% and precision scores above 91%. The system achieves 94.4% accuracy in tourist flow prediction, a response time of 16 s, and peak memory usage of 794 MB, outperforming comparative models. This approach enhances precision, prediction accuracy, and efficiency, offering an innovative solution for intelligent decision-making in tourism. Inderscience Publishers - linking academia, business and industry through research

Title: Smart tourism decision support system based on dual-heuristic algorithms

Authors: Qing Pan

Addresses: Department of Tourism, Chizhou Vocational and Technical College, Chizhou, 247100, China

Abstract: This study proposes an innovative tourism decision-support system driven by a dual-heuristic algorithm to overcome the subjectivity and low adaptability of traditional methods. The system integrates the analytic hierarchy process and an improved genetic algorithm to construct a scenic spot evaluation model. At the same time, a particle swarm optimisation algorithm enhances a back-propagation neural network for visitor flow prediction. Experiments show the model achieves losses of 0.026 and 0.023, with evaluation accuracies up to 92.47% and precision scores above 91%. The system achieves 94.4% accuracy in tourist flow prediction, a response time of 16 s, and peak memory usage of 794 MB, outperforming comparative models. This approach enhances precision, prediction accuracy, and efficiency, offering an innovative solution for intelligent decision-making in tourism.

Keywords: analytic hierarchy process; AHP; genetic algorithm; particle swarm optimisation; PSO; back propagation; digital tourism; decision support system.

DOI: 10.1504/IJICT.2026.153263

International Journal of Information and Communication Technology, 2026 Vol.27 No.37, pp.66 - 88

Received: 23 Oct 2025
Accepted: 13 Jan 2026
Published online: 29 Apr 2026 *

Title: Smart tourism decision support system based on dual-heuristic algorithms

Keep up-to-date