• Journal of Korean Institute of Industrial Engineers
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• v.38 no.2
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• pp.157-172
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• 2012

In most container terminals, containers are piled up and stored in a yard in order to utilize the space efficiently. Hence, it requires unproductive container-handling operations to retrieve a container that is not placed on the top of a container stack. As a result, to streamline container-loading operations by which containers are transferred from a yard to a vessel, it is necessary to pre-marshal (i.e., shuffle in advance) containers in accordance with container-loading plan. We propose $A^*$ algorithm to find the optimal container-relocation sequence for the intra-bay container pre-marshalling problem. To work out the heuristic estimate for the proposed $A^*$ algorithm, we introduce the container rearrangement problem and obtain the lower bound of the length of the optimal relocation sequence. The performance of the algorithm is validated extensively by the numerical experiments on the problem instances that are given in the previous studies and generated randomly with various parameters.

• Journal of Advanced Marine Engineering and Technology
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• v.23 no.5
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• pp.630-636
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• 1999

In this paper in optimal modulation controller for position control and anti-sway of container crane systems is designed by a recursive algorithm that determines the state weighting matrix Q of a linear quadratic performance. The optimal modulation controller is based on optimal control. The basic feature of the recursive algorithm is the reduction of the number of iterations as well as minimization of the calculations involved So in order to obtain a mathematical model which rep-resents the equation of motion of the trolley and load Lagrange equation is used. The optimal modulation controller has been verified and simulated to show that it is robust when a load dis-turbance is applied and a reference is changed.

• Journal of the Korean Society of Marine Environment & Safety
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• v.30 no.1
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• pp.118-126
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• 2024

In this paper, the research contents and results related to the automation of the hull-form optimal design of container ships are summarized. A container ship is a ship that generally operates near Froude number of 0.26. To implement hull-form optimal design automation for ships operating at this speed, an optimization algorithm, a hull-form change algorithm, a ship performance prediction algorithm, an automation algorithm, and an iterative calculation technique were applied to develop a numerical analysis computer program that enables hull-form optimal design automation of the container ship, and it was named HOTCONTAINER. In this study, a sensitivity analysis algorithm was developed and applied to appropriately set design variables for hull-form optimal design. To understand the reliability and real ship applicability of the developed algorithm, a numerical analysis was performed on KCS(KRISO Container Ship), a container ship that has been studied in various ways worldwide. Consequently, the optimal ship was derived, and the wave resistance, wave pattern, and wave height of the target and optimal ship were compared. In conclusion, compared the target ship, the optimal ship a 47.63% decrease in wave resistance, and the displacement and wet surface area decreased by 0.50% and 0.39%, respectively.

• IE interfaces
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• v.20 no.2
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• pp.204-215
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• 2007

This paper addresses vehicle routing planning in freight container transportation systems where a number of loaded containers are to be delivered to their destination places. The system under consideration is static in that all transportation requirements are predetermined at the beginning of a planning horizon. A two-phased procedure is presented for freight container transportation. In the first phase, the optimal model is presented to determine optimal total time to perform given transportation requirements and the minimum of number of vehicles required. Based on the results from the optimal model, in the second phase, ASA(Accelerated Simulated Annealing) algorithm is presented to perform all transportation requirements with the least number of vehicles by improving initial vehicle routing planning constructed by greedy method. It is found that ASA algorithm has an excellent global searching ability through various experiments in comparison with existing methods.

• Journal of Korean Institute of Industrial Engineers
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• v.24 no.1
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• pp.157-165
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• 1998

This paper considers the single-product production and transportation problem with discrete time, dynamic demand and finite time horizon, an extension of classical dynamic lot-sizing model. In the model, multiple freight container types are allowed as the transportation mode and each order (product) placed in a period is shipped immediately by containers in the period. Moreover, each container has type-dependent carrying capacity restriction and at most one container type is allowed in each shipping period. The unit freight cost for each container type depends on the size of its carrying capacity. The total freight cost is proportional to the number of each container type employed. Such a freight cost is considered as another set-up cost. Also, it is assumed in the model that production and inventory cost functions are dynamically concave and backlogging is not allowed. The objective of this study is to determine the optimal production policy and the optimal transportation policy simultaneously that minimizes the total system cost (including production cost, inventory holding cost, and freight cost) to satisfy dynamic demands over a finite time horizon. In the analysis, the optimal solution properties are characterized, based on which a dynamic programming algorithm is derived. The solution algorithm is then illustrated with a numerical example.

• Journal of Navigation and Port Research
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• v.28 no.6
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• pp.517-523
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• 2004

The container load planning is one of key factors for efficient operations of handling equipments at container ports. When the number of containers are large, finding a good solution using the conventional genetic algorithm is very time consuming. To obtain a good solution with considerably small effort, in this paper a pseudo-parallel genetic algorithm(PPGA) based on both the migration model and the ring topology is developed The performance of the PPGA is demonstrated through a test problem of determining the optimal loading sequence of the containers.

• IE interfaces
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• v.20 no.4
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• pp.525-538
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• 2007

The importance of efficient container transportation becomes more significant each year due to the constant growth of the global marketplace, and studies focusing on shipping efficiency are becoming increasingly important. In this paper, we propose an approach for vehicle scheduling that decreases the number of vehicles required for freight commerce by analyzing and scheduling optimal routes. Container transportation can be classified into round and single-trip transportation, and each vehicle can be linked in a specific order based on the vehicle state after completing an order. We develop a mathematical model to determine the required number of vehicles with optimal routing, and a heuristic algorithm to perform vehicle scheduling for many orders in a significantly shorter duration. Finally, we tested some numerical examples and compared the developed model and the heuristic algorithm. We also developed a decision support system that can schedule vehicles based on the heuristic algorithm.

• The Journal of Industrial Distribution & Business
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• v.13 no.12
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• pp.59-71
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• 2022

Purpose: Re-handling is an important factor that reduces the productivity of container terminals. The purpose of this paper is to propose an algorithm to find the order of container movement in order to minimize the number of re-handling in the process of carrying-out. Research design, data and methodology: This paper proposes an algorithm to set the optimal carry-out order and conducted tests to evaluate the performance of the algorithm proposed in this paper. 1. tests comparing the performance of an algorithm proposed in an existing study with that proposed in this paper. 2. Performance tests for bays with complex structures. Results: Test 1 shows that the algorithm proposed in this paper performs better than the existing algorithm. Test 2 shows that the proposed algorithm can also be used in bays with considerably high complexity and that there is no major problem with using it in the field. Conclusion: While we can conclude that the proposed algorithm as a carry-out algorithm is more effective than conventional methods, research is needed on how to handle more complex bays more effectively. This is because the larger the bay, the more container combinations increase, making it difficult to find the best carry-out order.

• Journal of the Korea Society of Computer and Information
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• v.20 no.10
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• pp.61-68
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• 2015

This paper deals with the pre-marshalling problem that the containers of container yard at container terminal are relocated in consensus sequence of loading schedule of container vessel. This problem is essential to improvement of competitive power of terminal. This problem has to relocate the all of containers in a bay with minimum number of movement. There are various algorithms such as metaheuristic as genetic algorithm and heuristic algorithm in order to find the solution of this problem. Nevertheless, there is no unique general algorithm that is suitable for various many data. And the main drawback of metaheuristic methods are not the solution finding rule but can be find the approximated solution with many random trials and by coincidence. This paper can be obtain the solution with O(m) time complexity that this problem deals with bin packing problem for m stack bins with descending order of take out ranking. For various experimental data, the proposed algorithm can be obtain the optimal solutions for all of data. And to conclude, this algorithm can be show that most simple and general algorithm with simple optimal solution finding rule.

• Journal of Navigation and Port Research
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• v.32 no.9
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• pp.737-742
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• 2008

In this paper, we deal with an allocation model of vertical type container yard for minimizing the total ATC (Automated Transfer Crane) working time and the equivalence of ATC working load in each block on automated container terminal. Firstly, a layout of automated container terminal yard is shown The characteristic of equipment which work in the terminal and its basic assumption are given Next, an allocation model which concerns with minimizing the total working time and the equivalence of working load is proposed for effectiveness of ATC working in automated container terminal. Also, a weight values on critical function are suggested to adjust the critical values by evaluating the obtained allocation plan. For ATC allocation algorithm, we suggest a simple repeat algorithm for on-line terminal operation.