Süt Taşımacılığında İnsan Sağlığını Koruma Odaklı Çoklu Ajanlı Yol Planlaması: Bulanık Mantık ve Hibrit Yaklaşımların Entegrasyonu

In transportation processes, delays and arbitrary decisions are often encountered, especially in the food and agriculture sectors. The prevailing focus of current navigation systems on speed or fuel efficiency often neglects the preservation of perishable and specialty products. This study aims to address these issues, particularly in milk transportation processes. It proposes decision-making through the use of specific standards such as efficiency, temperature, and mass, employing a dynamic framework. The study draws insights from the utilization of genetic algorithms, fuzzy logic, and hybrid approaches in multi-agent systems and autonomous robot path planning. Various aspects are explored in the literature, including coordination behaviors, fuzzy rule-based path planning, linguistic variables, and collaboration-based learning methods. The focus of this study lies in enhancing these fundamentals, particularly emphasizing on utilizing the A* algorithm with multi-target agents using fuzzy logic, aiming to provide robust solutions for multi-agent path planning scenarios.