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http://dx.doi.org/10.36498/kbigdt.2022.7.2.129

A Study on Stowage Automation Algorithm for Cargo Stowage Optimization of Vehicle Carriers  

JI Yeon Kim (동의대학교 대학원 인공지능학과)
Young-Jin Kang (동의대학교 인공지능그랜드ICT연구센터)
Jeong, Seok Chan (동의대학교 e비즈니스학과, 인공지능그랜드ICT연구센터, 부산IT융합부품연구소)
Hoon Lee ((주)토탈소프트뱅크 물류시스템 연구소)
Publication Information
The Journal of Bigdata / v.7, no.2, 2022 , pp. 129-137 More about this Journal
Abstract
With the development of the 4th industry, the logistics industry is evolving into a smart logistics system. However, ship work that transports vehicles is progressing slowly due to various problems. In this paper, we propose an stowage automation algorithm that can be used for cargo loading of vehicle carriers that shortens loading and unloading work time. The stowage automation algorithm returns the shortest distance by searching for a loading space and a movable path in the ship in consideration of the structure of the ship. The algorithm identifies walls, ramps and vehicles that have already been shipped, and can work even with randomly placed. In particular, it is expected to contribute to developing a smart logistics system for vehicle carriers by referring to the ship's master plan to search for vehicle loading and unloading space in each port and predict the shortest movable path.
Keywords
Stowage; Automation; Depth-First Search;
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