• Journal of the Korean Society of Industry Convergence
• /
• v.24 no.1
• /
• pp.19-29
• /
• 2021

In the Port Logistics system, Container Stowage planning is an important issue for cost-effective efficiency improvements. At present, Planners are mainly carrying out Stowage planning by manual or semi-automatically. However, as the trend of super-large container ships continues, it is difficult to calculate an efficient Stowage plan with manpower. With the recent rapid development of artificial intelligence-related technologies, many studies have been conducted to apply enhanced learning to optimization problems. Accordingly, in this paper, we intend to develop and present a Deep Q-Learning Network model for the Master Stowage planning of Container ships.

• Journal of the Society of Naval Architects of Korea
• /
• v.46 no.5
• /
• pp.520-526
• /
• 2009

Efficient stowage plan is required for handling large number of containers in a container terminal. Before a ship enters port, most of container terminals prepare a stowage plan based on information received from the shipping company. If this information does not have the accurate information of containers in the vessel, the stowage plan might be often changed or sometimes it becomes useless. In order to avoid this problem, we apply RFID system in the container ship and we propose a framework for communication between ships and terminals using RFID and Web Services technology.

• IE interfaces
• /
• v.19 no.4
• /
• pp.270-280
• /
• 2006

The shipping plan for an efficient augmentation of terminal is NP-hard problem which is subordinate to a shipping quantity. The load location problem and stowage planning problem are two important tactical problems for the efficient operations of container terminals. This paper is concerned with reduction of feasible region in constraints for stowage planning. After designing model which minimizes the number of shifting and the travel distance of the transfer crane, the simulated annealing algorithm is employed to search optimal solution quickly and accurately. In order to apply more realistic approach, the partial restriction through adding hatch is complemented to stowage planning decision problem applied in cluster. A variety of numerical experiments demonstrated that solutions by simulated annealing algorithm are useful and applicable in practice.

• Journal of Korean Port Research
• /
• v.9 no.1
• /
• pp.19-32
• /
• 1995

The objective of this paper is to suggest a decision support system allowing automated stowage planning for containerships, and provide a working prototype. Unlike most previous works in this topic which concentrated mainly on the theoretical aspects. this paper attempts to develop a feasible system for improving the speed and accuracy of stowage planning by combining practice and theoretical solution methods. The paper includes a definition of the containership stowage problem, and details on the design and development of the automated stowage plan generation routine. Several program tests are undertaken with randomly generated input data. The results suggest that the prototype system is quite meaningful even though there are still some unsolved problems. The paper concludes with a discussion of issues for future development of the decision support system.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• 2022.11a
• /
• pp.334-335
• /
• 2022

Among domestic car carrier operating shipping companies, some shipping companies are operating a stowage planning system that is installed and executed on a computer, and most shipping companies are executing stowage plans with documents such as Excel. This is a study on how to utilize web service technology so that multiple users can use the planning system more efficiently in the cargo stowage planning process for car carriers.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• 2009.06a
• /
• pp.165-166
• /
• 2009

The purpose of this study is to develop a model of the optimal stowing plan for car carriers. This model will be used for an integrated model of maritime transportation planning for car carriers with vessel allocation and voyage planning models.

• The Journal of Bigdata
• /
• v.8 no.2
• /
• pp.27-36
• /
• 2023

The logistics industry is becoming increasingly important as it is closely linked to our daily lives, storing and transporting the goods and resources that businesses and consumers need. With its growing importance, the logistics industry strives to provide efficient and sustainable services through innovations and artificial intelligence are being used to optimize logistics networks, make transport more environmentally friendly, and more. Research and improvements are being undertaken in various domains, such as logistics network optimization and environmentally friendly transportation through technological innovation and artificial intelligence; however, there still needs to be more research in certain aspects of the logistics industry. In particular, devising an optimized stowage plan for vehicle carriers, considering various factors, involves a significant degree of complexity and remains an under-researched area. This paper studies the loading and unloading algorithms that enable to quickly and efficiently establish stowage plans for vehicle carriers, reflecting a variety of considerations and rules for stowage planning.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.28 no.4
• /
• pp.31-37
• /
• 2003

This paper deals with a stowage plan for plates in a warehouse. This plan includes how to place each plate and how to sequence outgoing lots for picking. A group of plates in an outgoing lot should be loaded in the same outgoing pallet and between two elates in the same lot, no plate from other than the lot should be placed. Since the approach to the plates is only from above, when the plates in the different lots are placed mixed in a warehouse, we have to temporarily move many of plates in some other place to let a plate in the lot for which loading is under way go out. Our purpose is to minimize those temporary moves. We analyze the computational complexity of several problems arising in the stowage plan of a plate warehouse.

• The Journal of Bigdata
• /
• v.7 no.2
• /
• pp.129-137
• /
• 2022

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.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.17 no.6
• /
• pp.1259-1266
• /
• 2022

Stowage planning is an essential process for safe loading by establishing, agreeing on, and systematically implementing a reasonable loading and securing method based on information on cargo, loading/unloading and the ship. In addition, depending on the plan, there may be a difference of about 14% or more in the loading amount per ship, which causes a tolerance rate and leads to an increase in sea freight charges. In this study, work environment and process standards for steel coil shipment, and classification regulations and guidelines related to steel coil shipment were analyzed. In addition, we developed a steel coil loading and placement automation system that derives an optimal loading plan through performance data-based shipping balancing and stability analysis.