A Review on The Use of Artificial Intelligence and Machine Learning Technologies in The Logistics Sector

Suzan Oğuz; Deniz Yalçıntaş

Makale detayları

A Review on The Use of Artificial Intelligence and Machine Learning Technologies in The Logistics Sector

Yazarlar:

Suzan Oğuz | Deniz Yalçıntaş

Yayıncı:

Ataturk University

Ana Başlıklar:

İş Sistemleri (Diğer)

Dergi:

Trends in Business and Economics Vol.38 Issue 4, pp.218-225

Belge Tipi:

Makale

Yayın Tarihi:

10/2024

Belge Dili:

İngilizce

Document ID (Org No.):

2001328962

pISSN:

2822-2652

Anahtar kelimeler:

Özet:

 In recent years, developments in Artificial Intelligence AI and MachineLearning ML technologies have had profound effects on all sectors. The logistics industry has also become a sector where these technologies are being used to a significant extent. The emergence of intelligent logistics systems offers several opportunities for the advancement of this sector by facilitating digital transformation in supply chain and logistics. The aim of this study is to provide a comprehensive review of recent studies examining the use of AI and ML systems in the logistics industry. In this study, which is designed as a systematic study, firstly, based on the existing literature, the basic concepts, trends, researchers and countries working on AI and ML systems in the logistics sector are examined by bibliometric analysis method. Then, information about the prominent AI and ML systems in logistics is given. It is seen that the most frequently used AI and ML technologies in logistics are Deep Learning, Optimization, Internet of Things IoT, Data Mining and Predictive Models. The methodologies presented in the study have a practical importance in increasing efficiency, transparency and planning in the logistics.

 In recent years, developments in Artificial Intelligence AI and MachineLearning ML technologies have had profound effects on all sectors. The logistics industry has also become a sector where these technologies are being used to a significant extent. The emergence of intelligent logistics systems offers several opportunities for the advancement of this sector by facilitating digital transformation in supply chain and logistics. The aim of this study is to provide a comprehensive review of recent studies examining the use of AI and ML systems in the logistics industry. In this study, which is designed as a systematic study, firstly, based on the existing literature, the basic concepts, trends, researchers and countries working on AI and ML systems in the logistics sector are examined by bibliometric analysis method. Then, information about the prominent AI and ML systems in logistics is given. It is seen that the most frequently used AI and ML technologies in logistics are Deep Learning, Optimization, Internet of Things IoT, Data Mining and Predictive Models. The methodologies presented in the study have a practical importance in increasing efficiency, transparency and planning in the logistics.

 In recent years, developments in Artificial Intelligence AI and MachineLearning ML technologies have had profound effects on all sectors. The logistics industry has also become a sector where these technologies are being used to a significant extent. The emergence of intelligent logistics systems offers several opportunities for the advancement of this sector by facilitating digital transformation in supply chain and logistics. The aim of this study is to provide a comprehensive review of recent studies examining the use of AI and ML systems in the logistics industry. In this study, which is designed as a systematic study, firstly, based on the existing literature, the basic concepts, trends, researchers and countries working on AI and ML systems in the logistics sector are examined by bibliometric analysis method. Then, information about the prominent AI and ML systems in logistics is given. It is seen that the most frequently used AI and ML technologies in logistics are Deep Learning, Optimization, Internet of Things IoT, Data Mining and Predictive Models. The methodologies presented in the study have a practical importance in increasing efficiency, transparency and planning in the logistics.

 Son yıllarda yapay zekâ ve makine öğrenimi teknolojilerindeki gelişmelerin tüm sektörlerde derin etkileri bulunmaktadır. Lojistik sektörü de bu teknolojilerin önemli ölçüde kullanıldığı bir sektör haline gelmiştir. Akıllı lojistik sistemlerinin ortaya çıkışı, tedarik zinciri ve lojistik alanında dijital dönüşümü kolaylaştırmasıyla bu sektörün ilerlemesi için çeşitli fırsatlar sunmaktadır. Bu çalışmanın amacı lojistik sektöründe yapay zekâ ve makine öğrenimi sistemlerinin kullanımını inceleyen güncel çalışmaları kapsamlı bir şekilde incelemektir. Sistematik bir çalışma olarak tasarlanan bu çalışmada öncelikle mevcut literatürden yola çıkılarak lojistik sektöründe yapay zekâ ve makine öğrenimi sistemleri ile ilgili temel kavramlar, eğilimler, bu konuda çalışma yapan araştırmacılar ve ülkeler bibliyometrik analiz yöntemiyle incelenmiştir. Daha sonra lojistikte öne çıkan yapay zekâ ve makine öğrenimi sistemleri ile ilgili bilgilere yer verilmiştir. Lojistikte en sık kullanılan yapay zeka ve makine öğrenimi teknolojilerinin derin öğrenme, optimizasyon, nesnelerin interneti, veri madenciliği ve tahmin modelleri olduğu görülmektedir. Çalışmada sunulan metodolojiler lojistikte verimliliği, şeffaflığı ve planlanmayı arttırmada pratik bir öneme sahiptir.

Makale detayları

A Review on The Use of Artificial Intelligence and Machine Learning Technologies in The Logistics Sector

Yazarlar:

Suzan Oğuz | Deniz Yalçıntaş

Yayıncı:

Ataturk University

Ana Başlıklar:

İş Sistemleri (Diğer)

Dergi:

Trends in Business and Economics Vol.38 Issue 4, pp.218-225

Belge Tipi:

Makale

Yayın Tarihi:

10/2024

Belge Dili:

İngilizce

Document ID (Org No.):

2001328962

pISSN:

2822-2652

Logistics

Artificial Intelligence

Machine Learning

Technology

Bibliometric AnalysisLojistik

Yapay Zekâ

Makine Öğrenimi

Teknoloji

Bibliyometrik Analiz

Sayı

Makale detayları

Yazarlar: Suzan Oğuz | Deniz Yalçıntaş

Yayıncı: Ataturk University

Ana Başlıklar: İş Sistemleri (Diğer)

Dergi: Trends in Business and Economics Vol.38 Issue 4, pp.218-225

Belge Tipi: Makale

Yayın Tarihi: 10/2024

Belge Dili: İngilizce

Document ID (Org No.): 2001328962

pISSN: 2822-2652

Sayı

Yazarlar:

Suzan Oğuz | Deniz Yalçıntaş

Yayıncı:

Ataturk University

Ana Başlıklar:

İş Sistemleri (Diğer)

Dergi:

Trends in Business and Economics Vol.38 Issue 4, pp.218-225

Belge Tipi:

Makale

Yayın Tarihi:

10/2024

Belge Dili:

İngilizce

Document ID (Org No.):

2001328962

pISSN:

2822-2652