Towards AI driven environmental sustainability: an application of automated logistics in container port terminals

Naoum Tsolakis, Dimitris Zissis, Spiros Papaefthimiou, Nikolaos Korfiatis

Research output: Contribution to journalArticlepeer-review

Abstract

Artificial intelligence and data analytics capabilities have enabled the introduction of automation, such as robotics and Automated Guided Vehicles (AGVs), across different sectors of the production spectrum which successively has profound implications for operational efficiency and productivity. However, the environmental sustainability implications of such innovations have not been yet extensively addressed in the extant literature. This study evaluates the use of AGVs in container terminals by investigating the environmental sustainability gains that arise from the adoption of artificial intelligence and automation for shoreside operations at freight ports. Through a comprehensive literature review, we reveal this research gap across the use of artificial intelligence and decision support systems, as well as optimisation models. A real-world container terminal is used, as a case study in a simulation environment, on Europe’s fastest-growing container port (Piraeus), to quantify the environmental benefits related to routing scenarios via different types of AGVs. Our study contributes to the cross-section of operations management and artificial intelligence literature by articulating design principles to inform effective digital technology interventions at non-automated port terminals, both at operational and management levels.

Original languageEnglish
Pages (from-to)1-21
Number of pages21
JournalInternational Journal of Production Research
Early online date25 Apr 2021
DOIs
Publication statusE-pub ahead of print - 25 Apr 2021

Keywords

  • Automated Guided Vehicles
  • artificial intelligence
  • container port management
  • environmental sustainability
  • intelligent port logistics
  • vehicle routing

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