Title: Deep learning in logistics: a systematic review

Authors: Khaoula Sahraoui; Samia Aitouche; Karima Aksa

Addresses: Laboratory of Automation and Manufacturing (LAP), Industrial Engineering Department, University Batna 2, Rue Mohamed Boukhlouf, 05000, Batna, Algeria ' Laboratory of Automation and Manufacturing (LAP), Industrial Engineering Department, University Batna 2, Rue Mohamed Boukhlouf, 05000, Batna, Algeria ' Laboratory of Automation and Manufacturing (LAP), Industrial Engineering Department, University Batna 2, Rue Mohamed Boukhlouf, 05000, Batna, Algeria

Abstract: Logistics is one of the main tactics that countries and businesses are improving in order to increase profits. Another prominent theme in today's logistics is emerging technologies. Today's developments in logistics and industry are how to profit from collected and accessible data to use it in various processes such as decision making, production plan, logistics delivery programming, and so on, and more specifically deep learning methods. The aim of this paper is to identify the various applications of deep learning in logistics through a systematic literature review. A set of research questions had been identified to be answered by this article.

Keywords: logistics; deep learning; state of the art; systematic literature review; SLR.

DOI: 10.1504/IJLSM.2024.136489

International Journal of Logistics Systems and Management, 2024 Vol.47 No.2, pp.246 - 266

Received: 08 Sep 2020
Accepted: 30 Mar 2021
Published online: 05 Feb 2024 *

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