Afet Lojistiği, İnsani Yardım Lojistiği ve Yardım Lojistiği Alanlarında Yapay Zekâ ve Makine Öğrenmesi Tekniklerinin Kullanımı: Sistematik Literatür Taraması

Öz

Çalışmanın amacı afet lojistiği, insani yardım lojistiği ve yardım lojistiği alanlarında yapay zekâ ve makine öğrenmesi tekniklerinin kullanımına ilişkin literatürü incelemek ve araştırma eğilimleri ile boşlukları ortaya koymaktır. Web of Science (WoS) veri tabanında geçmişten 2025 yılı sonunu kapsayacak şekilde yapılan sistematik literatür taramasında 35 makaleye ulaşılmıştır. İki aşamalı analiz sürecinin ilk aşamasında makaleler anahtar kelime, yayın yılı, ülke ve odaklanılan temalar itibariyle analiz edilmiştir. İkinci aşamada makaleler daha detaylı incelenerek afetlerle ilgili hangi yapay zekâ ve makine öğrenmesi tekniklerinin hangi tip karar problemlerinde kullanıldığı belirlenmiştir. Bulgular afet lojistiğinde tahminleme, rotalama ve tahliye planlaması, ağ tasarımı ve dağıtım planlaması gibi problemler ile karar destek sistemlerinin oluşturulmasında yapay zekâ ve makine öğrenmesi tekniklerinden yoğun olarak faydalanıldığını göstermiştir. Çalışmanın; mevcut durumu ortaya koyarak afet lojistiği, insani yardım lojistiği ve yardım lojistiği alanlarında gelecekte yapılacak araştırmalar için yol gösterici olması beklenmektedir.

Anahtar Kelimeler

• Afet lojistiği
• İnsani yardım lojistiği
• Yardım lojistiği
• Yapay zekâ
• Makine öğrenmesi

Teşekkür

Bu makale, Niğde Ömer Halisdemir Üniversitesi Sosyal Bilimler Enstitüsü’nde Yasin Afşar tarafından, Prof. Dr. Arzum Büyükkeklik danışmanlığında ve Doç. Dr. Ahmet Şakir Dokuz ikinci danışmanlığında hazırlanan doktora tezinden üretilmiştir.

The Use of Machine Learning and Artificial Intelligence Techniques in Disaster Logistics, Humanitarian Logistics, Relief Logistics: Systematic Literature Review

Öz

The aim of this study is to review the existing literature on the use of artificial intelligence and machine learning techniques in disaster logistics, humanitarian logistics, and relief logistics, and to identify prevailing research trends and gaps. In a systematic literature review conducted using the Web of Science (WoS) database covering the period from its inception through the end of 2025, a total of 35 articles were identified. In the first stage of the two-phase analysis process, the articles were analyzed in terms of keywords, publication year, country, and thematic focus. In the second stage, the articles were examined in greater depth to determine which artificial intelligence and machine learning techniques were applied to which types of disaster related decision problems. The findings indicate that artificial intelligence and machine learning techniques are extensively used in addressing problems such as disaster related forecasting, routing and evacuation planning, network design, and distribution planning, as well as in the development of decision support systems. By presenting the current state of the literature, this study is expected to provide guidance for future research in the fields of disaster logistics, humanitarian logistics, and relief logistics.

Anahtar Kelimeler

• Disaster logistics
• Humanitarian logistics
• Relief logistics
• Artificial intelligence
• Machine learning

Kaynakça

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