Deniz Lojistiğinde Yapay Zeka Uygulamalarının Etkileri

Year 2022, Issue: 34, 217 - 225, 31.03.2022

Batin Latif Aylak

https://doi.org/10.31590/ejosat.1079206

Cited By: 1

Abstract

Bu çalışma, deniz taşımacılığı problemlerini çözmek için Yapay Zeka yöntemlerinin kullanımındaki güncel yaklaşımları belirlemeyi amaçlamaktadır. Yapay zekadaki son gelişmeler incelenerek deniz lojistiğine uyarlanma şekli gözden geçirilmektedir. Bu çalışmada denizcilik endüstrisinde yapay zeka ile ilgili 66 makale bibliyometrik olarak incelenmiştir. Araştırma verileri öncelikle IEEE Xplore, Web of Science, ScienceDirect (Elsevier), Sciences Citation Index, Google Scholar, Springer ve ilgili dergilerin veritabanlarından elde edilmiştir. Seçilen makaleler kategorize edilerek tasnif edilmiş ve bazı önemli yayınların sonuçları ayrıntılı olarak tartışılmıştır. Araştırma boşluklarını vurgulayan ve gelecekteki araştırma yönelimlerini tahmin eden kapsamlı bir değerlendirme de sunulmaktadır. Yapay zeka kullanan daha fazla araştırma için denizcilik endüstrisinde iki olası alan önerilmiştir. Tahmine dayalı analiz ilk alandır ve bunu enerji verimliliği optimizasyonu takip etmektedir. Buna ek olarak, Makine Öğrenmesi ve Yöneylem Araştırması yüksek düzeyde uzmanlaşmış buluşsal yöntemler oluşturmak için pahalı ve verimsiz insan emeğine duyulan ihtiyacı önlemek için optimizasyon sorunlarını çözmek için buluşsal yöntemlerin öğrenilmesini otomatikleştirmeye yönelik artan bir ilgiyi teşvik etmiştir. Gelecekteki araştırmalar, sürekli artan miktarda mevcut veriyi kullanarak Denizcilik Lojistiği sorunlarını ele almak için bu yeni makine öğrenmesi yaklaşımlarından yararlanabilir. Deniz lojistiği ile ilgili gelecekteki araştırmalar, belirlenen boşluklara dayalı öğrenme modelleri de geliştirebilir.

Keywords

Yapay Zeka, Otomatik Bilgi Sistemi, Literatür Araştırması, Makine Öğrenmesi, Deniz Lojistiği

The Impacts of the Applications of Artificial Intelligence in Maritime Logistics

Abstract

This study aims to identify current approaches in the usage of Artificial Intelligence (AI) methods for solving shipping problems. Recent advances in AI are being examined, and the way it is adapted to maritime logistics is reviewed. In this study, 66 papers dealing with AI in the maritime industry are reviewed bibliometrically. Research data were primarily sourced from databases of IEEE Xplore, Web of Science, ScienceDirect (Elsevier), Sciences Citation Index, Google Scholar, Springer, and journals. Selected papers are categorized and classified, and the outcomes of some noteworthy publications are discussed in detail. A comprehensive assessment is also presented, which highlights research gaps and forecasts future research orientations. Two possible areas in the maritime industry are proposed for further research using AI capabilities. Predictive analysis is the first domain, followed by energy efficiency optimization. In addition, Machine Learning (ML) and Operations Research (OR) have fostered a growing interest in automating the learning of heuristics to solve optimization problems to avoid the need for expensive and inefficient human labour to create highly specialized heuristics. Future research can take advantage of these new ML approaches to address Maritime Logistics problems utilizing the ever-increasing amount of data available. Future research on maritime logistics can also develop learning models based on the identified gaps.

Keywords

Artificial Intelligence, Automated Information System, Literature Review, Machine Learning, Maritime Logistics

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