Food Waste Reduction AI Technologies in Restaurant Management: An MS-TORO Approach

This study analyzes artificial intelligence (AI)-based technologies for food waste reduction in restaurant management, particularly in the case of the Philippines. Using the multiple-stakeholder target-oriented robust-optimization (MS-TORO) approach, AI solutions are ranked based on cost, feasibility, infrastructure requirements, and effectiveness. The key findings highlight that Too Good To Go is the most practical AI solution due to its affordability and focus on surplus food redistribution, making it ideal for resource-limited settings. The study emphasizes the need for government support, financial incentives, and public–private partnerships to facilitate AI adoption. Additionally, integrating AI-driven waste reduction with food security initiatives and sustainability projects can enhance their impact. Addressing economic and infrastructural challenges is crucial for maximizing AI’s potential in food waste management in developing economies.