• Title/Summary/Keyword: 컨테이너화물조작장

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LCL Cargo Loading Algorithm Considering Cargo Characteristics and Load Space (화물의 특성 및 적재 공간을 고려한 LCL 화물 적재 알고리즘)

  • Daesan Park;Sangmin Jo;Dongyun Park;Yongjae Lee;Dohee Kim;Hyerim Bae
    • Journal of Intelligence and Information Systems
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    • v.29 no.4
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    • pp.375-393
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    • 2023
  • The demand for Less than Container Load (LCL) has been on the rise due to the growing need for various small-scale production items and the expansion of the e-commerce market. Consequently, more companies in the International Freight Forwarder are now handling LCL. Given the variety in cargo sizes and the diverse interests of stakeholders, there's a growing need for a container loading algorithm that optimizes space efficiency. However, due to the nature of the current situation in which a cargo loading plan is established in advance and delivered to the Container Freight Station (CFS), there is a limitation that variables that can be identified at industrial sites cannot be reflected in the loading plan. Therefore, this study proposes a container loading methodology that makes it easy to modify the loading plan at industrial sites. By allowing the characteristics of cargo and the status of the container to be considered, the requirements of the industrial site were reflected, and the three-dimensional space was manipulated into a two-dimensional planar layer to establish a loading plan to reduce time complexity. Through the methodology presented in this study, it is possible to increase the consistency of the quality of the container loading methodology and contribute to the automation of the loading plan.

Logistics Peculiarities for the Firms in the Daegu-Gyeongbuk Area (대구.경북지역 기업의 물류특성 분석)

  • Ha, Yeong-Seok;Seo, Jung-Soo
    • Journal of Korea Port Economic Association
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    • v.27 no.2
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    • pp.241-260
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    • 2011
  • This paper qualitatively describes logistics behaviors of 113 companies located in Daegu-Gyeongbuk by considering various characteristics such as business location, trade volume, cargo types and the possession of company's own warehouse. A logit model is developed to investigate how predictor variables affect these companies' inclination of utilizing Third Party Logistics Provider(3PL). The estimation results of 102 effective data points show that among the four predictors the location of company's HQs (HQADD) and trade volume (TRDTEU) significantly increase company's tendency towards utilizing 3PL while the remaining two variables (BULK, WAREHS) imparting statistically insignificant influence. The results indicate that those companies located outside the region tend to implement a strategy of using more 3PL and also that the larger the trade volume of the company the more 3PL the company uses to improve the efficiency in logistics.