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<p>This study proposes Halal Phuket, an AI-driven route recommendation system for Shariah-compliant tourism planning. We formalize halal itinerary planning as a constrained multi-objective optimization problem and solve it using a governance-embedded genetic algorithm, where Prayer-time Satisfaction (SMS) functions as both a utility component and a feasibility-shaping constraint; validation is conducted via 30-run benchmarking against multiple baselines with non-parametric statistical significance testing. Islamic governance is operationalized through the Quranic Rational Unified Process (QuRUP) by translating jurisprudential Ahkam into computable admissibility rules that filter non-compliant venues before search. To quantify worship feasibility, we introduce Prayer-time Satisfaction (SMS) as a route-level metric integrated into the fitness function and constraint-handling mechanism. The optimizer uses a Genetic Algorithm with domain-specific repair operators, fuzzy preference modeling, and a generative explanation layer that produces human-readable itinerary rationales. The system is validated on a curated dataset of 295 venues in Phuket Province, Thailand (mosques, halal restaurants, hotels, and attractions). Across 30 independent runs, the proposed HCIOP‑GA achieves the highest mean fitness among seven baselines, including NSGA‑II, MOEA/D, and an RL routing baseline, while preserving strong constraint satisfaction (SMS ≥ 0.85) and high halal compliance; differences are assessed using non‑parametric statistical testing.</p>

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Design and implementation of artificial intelligence system for halal travel route recommendation

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年5月7日

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  • Nasith Laosen,
  • Tanagrit Chansaeng,
  • Pita Jarupunphol

摘要

This study proposes Halal Phuket, an AI-driven route recommendation system for Shariah-compliant tourism planning. We formalize halal itinerary planning as a constrained multi-objective optimization problem and solve it using a governance-embedded genetic algorithm, where Prayer-time Satisfaction (SMS) functions as both a utility component and a feasibility-shaping constraint; validation is conducted via 30-run benchmarking against multiple baselines with non-parametric statistical significance testing. Islamic governance is operationalized through the Quranic Rational Unified Process (QuRUP) by translating jurisprudential Ahkam into computable admissibility rules that filter non-compliant venues before search. To quantify worship feasibility, we introduce Prayer-time Satisfaction (SMS) as a route-level metric integrated into the fitness function and constraint-handling mechanism. The optimizer uses a Genetic Algorithm with domain-specific repair operators, fuzzy preference modeling, and a generative explanation layer that produces human-readable itinerary rationales. The system is validated on a curated dataset of 295 venues in Phuket Province, Thailand (mosques, halal restaurants, hotels, and attractions). Across 30 independent runs, the proposed HCIOP‑GA achieves the highest mean fitness among seven baselines, including NSGA‑II, MOEA/D, and an RL routing baseline, while preserving strong constraint satisfaction (SMS ≥ 0.85) and high halal compliance; differences are assessed using non‑parametric statistical testing.