• 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.

• Korean Journal of Computational Design and Engineering
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• v.21 no.2
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• pp.177-185
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• 2016

In this paper, an optimal planning system for operating transporters in shipyard is developed. The system is designed to utilize the geometries of shipyard, and manage the data of blocks and transporters directly. There are four major menus such as shipyard map management based on GIS, block transportation request, transporter management, and optimal transportation planning in the system. The geometries and properties of the shops, roads, and addresses are manipulated in the shipyard map management menu. The block transportation requests and the properties of transporters are managed in the block transportation request and transporter management menus, respectively. The optimum transportation is planned automatically for minimizing the unload times of the transporters, and the optimum transportation plans are confirmed and printed to the transporter drivers. The effectiveness of the system was verified through the application to a large-sized shipyard.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2006.10a
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• pp.240-257
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• 2006

In an effort to gain competitiveness, recently many companies are trying to outsource their logistics activities to the logistics specialists, while concentrating on their core and strategic business area. Because of this trend, the third party logistics comes to the fore, catching people's attention, and expanding its market rapidly. Under these circumstances, the third party logistics companies are making every effort to improve their logistics services and to develop an information system in order to enhance their competitiveness. In particular, among these efforts one of the critical parts is the decision support system for effective transportation network planning. To this end, this study has developed an efficient decision support system for an optimal transportation network planning by comprehensively considering the transportation mode, routing, assignment, and schedule. As a result of this study, the new system enables the expansion of the third party logistics companies' services including the multimodal transportation, not to mention one mode of transportation, and also gets them ready to plan an international transportation network.

• Journal of Navigation and Port Research
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• v.32 no.4
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• pp.295-304
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• 2008

In order to achieve a sustainable competitive advantage in the expanding maritime transportation market, most shipping companies are making every effort to reduce transportation costs. Likewise, the car shipping companies, which carry more than 80% of total car import and export logistics volume, also do their utmost for transportation cost saving. Until now many researches have been made for efficient maritime transportation, but studies for car shipping companies have rarely been made. For this reason, this study has tried to develop a maritime transportation planning support system which can help to save logistics costs and increase a competitive power of car shipping companies. To this end, instead of manual effort to solve the routing problem of car carrier vessels, this study has used an integer programming model to make an optimal transportation planning at the minimum cost. Also in response to the frequent changes both in the car production schedule and ship's arrival schedule after the completion of transportation planning, this research has developed a decision support system of maritime transportation, so that users can easily modify their existing plans.

• Journal of the Society of Naval Architects of Korea
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• v.50 no.5
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• pp.298-306
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• 2013

Nowadays, a transporter manager plans the schedule of the block transportation by considering the experience of the manager, the production process of the blocks and the priority of the block transportation in shipyard. The schedule planning of the block transportation should be rearranged for the reflection of the path blocking cases occurred by unexpected obstacles or delays in transportation. In this paper, the optimal block transportation path planning system is developed for rearranging the schedule of the block transportation by considering the damaged path. $A^*$ algorithm is applied to calculate the new shortest path between the departure and arrival of the blocks transported through the damaged path. In this algorithm, the first node of the damaged path is considered as the starting position of the new shortest path, and then the shortest path calculation is completed if the new shortest path is connected to the one of nodes in the original path. In addition, the data structure for the algorithm is designed. This optimal block transportation path planning system is applied to the Philippine Subic shipyard and the ability of the rapid path modification is verified.

• Journal of the Korean Operations Research and Management Science Society
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• v.3 no.1
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• pp.69-73
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• 1978

This paper deals with the problem of determining the optimal inventory-transportation policy of the idealistically simple inventory-transportation system with the following assumptions: (1) The system consists of a single central warehouse and a single local warehouse, (2) The planning horizon is finite, (3) Demand rate is fixed costant, and so forth. Developed is the algorithm by which to identify the optimal inventory policy which minimizes the total cost incurred to the system over the given finite planning horizon. A sample numerical example is presented along with a discussion of the possible applications of the approach used n the algorithm.

• IE interfaces
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• v.16 no.2
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• pp.174-184
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• 2003

This paper addresses a fleet operation planning problem for a static freight container transportation system in which all the transportation requirements are predetermined at the beginning of a planning horizon. In the transportation system under consideration, a number of loaded containers are to be moved between container storage yards. An optimal fleet planning model is used to determine the minimum number of vehicles required. Based on the results from the optimal model, a tabu-search based algorithm is presented to perform a given transportation requirements with the least number of vehicles. The performance of the new procedure is evaluated through some experiments in comparison with two existing methods, and the it is found that our procedure produces good-quality solutions.

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

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.05a
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• pp.159-166
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• 2006

The aim of synchronization of production and transportation planning in the supply chain is to increase the flexibility and to decrease various costs. The suggested model in this study synchronizes the timing to supply to a downstream manufacturer directly after production and to be consumed in a downstream manufacturer right after receipt. This model deals with the frequent delivery in small amount which is a new trend of the transportation not governed the economy of scale principle. Moreover, various types of transportation governed by the economy of scale principle or not are considered. Then, the two-phase mathematical model is suggested to obtain optimal job sequence and production quantity for each tasks. But, it is difficult to gain optimal solutions if there is a transportation governed by the economy of scale principle in the supply chain, or the size of the problem is increased. Thus, heuristic algorithms based on simulated annealing and genetic algorithm are suggested to find good solutions in the reasonable time.

• Journal of Korean Society of Transportation
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• v.12 no.1
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• pp.75-84
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• 1994

In this paper we address the issue of how an optimal sample size computation relates the level of precision required for travel demand estimations and transportation planning. We approach the problem by 1) deriving a theoretical solution, 2) developing a computational procedure (algorithm) to implement the theoretical solution, and 3) demonstrating a practical application. Ultimately, we construct a formal scheme of optimal sample size computation for use in travel data collection processe.