Multi-Agent Route Planning Focused on Protecting Human Health in Milk Transportation: Integration of Fuzzy Logic and Hybrid Approaches

Year 2024, Volume: 3 Issue: 2, 17 - 34, 30.12.2024

Cem Özkurt

https://doi.org/10.5281/zenodo.14585359

Abstract

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.

Keywords

Mobile Path Planning , Pathfinding with A* algorithms , Multi-Target Agents Path Planning , Fuzzy Logic

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

Abstract

Genellikle taşıma süreçlerinde yaşanan gecikmeler veya keyfi kararlar, özellikle gıda ve tarım sektörlerinde sıkça karşılaşılan bir sorundur. Mevcut navigasyon sistemlerinin genellikle sadece hız veya yakıt tasarrufu odaklı olması, kısa ömürlü ve özel ürünlerin korunmasını ihmal etmesine neden olmaktadır. Bu çalışma, özellikle süt taşıma süreçlerinde ortaya çıkan bu sorunlara çözüm getirmeyi hedeflemektedir. Süt taşımacılığında, verim, sıcaklık ve kütlenin kullanımı gibi belirli standartlar belirlenerek, dinamik bir yapı kullanılarak karar alınması önerilmektedir. Çalışma, genetik algoritmalar, bulanık mantık ve hibrit yaklaşımların çoklu ajan sistemleri ve otonom robot yol planlamasında kullanımına dair önemli perspektiflere dayanmaktadır. Literatürde, koordinasyon davranışları, bulanık kurallı yol planlaması, dil değişkenleri ve işbirliğine dayalı öğrenme yöntemleri gibi çeşitli alanlar incelenmektedir. Bu çalışmanın odaklandığı konu, "A* algoritması ile çoklu hedefli ajanları
kullanarak bulanık mantık" üzerine yoğunlaşarak, bu temelleri daha da geliştirmeyi ve çoklu ajanlı yol planlama senaryoları için güçlü çözümler sunmayı amaçlamaktadır.

Keywords

Mobil Yol Planlaması , A* algoritması ile Yol Bulma , Çok Hedefli Ajanlar Yol Planlaması , Bulanık Mantık

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