• Journal of the Korean Institute of Navigation
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• v.24 no.5
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• pp.385-395
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• 2000

In the transportation literature, many useful decision making models for ship routing and ship scheduling have been studied. But the majority of these studies are on industrial carriers, bulk carriers, or tankers. It is quite recent that a few optimization models have been developed for liner fleet routing and scheduling problems. However there have been few academic studies on decision making models for the routing or scheduling problems of passenger ships in spite of their economic importance in the entire shipping industry. The purpose of this study is to develop analytic decision making models for ship routing and scheduling for the passenger ship fleet. This study gives two optimization models, one is a linear programming model and the other a goal programming model. These two models are solved easy by commercial linear programming softwares and suggest optimal ship routing plans and many other useful implications for passenger ship fleet managers.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.9
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• pp.767-773
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• 2014

An economic ship routing means to sail a ship with a goal of minimizing the fuel consumption by utilizing weather forecast information, and there have been various systems which have been recently studied. For a successful economic ship routing system, it is needed to properly control an engine power or change a geographical path considering weather forecast. An optimal geographical path is difficult to be determined, though, because it is a minimal dynamic-cost path search problem where the actual fuel consumption is dynamically variable by the weather condition when the ship will pass the area. In this paper, we propose an geographical path-search algorithm based on evolutionary strategy to efficiently search a good quality solution out of tremendous candidate solutions. We tested our approach with the shortest path-based sailing method over seven testing routes and observed that the former reduced the estimated fuel consumption than the latter by 1.82% on average and the maximum 2.49% with little difference of estimated time of arrival. In particular, we observed that our method can find a path to avoid bad weather through a case analysis.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.4B
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• pp.412-421
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• 2011

An economic ship routing means to sail a ship with a goal of minimizing the fuel consumption by utilizing weather forecast information, and many such systems have been recently developed. Most of them assume that sailing is carried out with a constraint like a fixed output of engine-power or a fixed sailing speed. However, if the output of engine-power is controlled, it is possible to reduce the fuel consumption by sailing a ship under a relatively good weather condition. In this paper, we propose a novel economic ship routing system which can search optimal outputs of the engine-power for each part of a path by employing an evolutionary strategy. In addition, we develope an $A^*$ algorithm to find the shortest path and a method to enhance the degree of curve representation. These make the proposed system applicable to an arbitrary pair of departure and destination points. We compared our proposed system with another existing system not controlling output of the engine-power over 36 scenarios in total, and observed that the former reduced the estimated fuel consumption than the latter by 1.3% on average and the maximum 5.6% with little difference of estimated time of arrival.

• KIPS Transactions on Computer and Communication Systems
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• v.1 no.2
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• pp.79-86
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• 2012

An economic ship routing means to sail a ship with a goal of minimizing the fuel consumption by utilizing weather forecast information, and various such systems have been recently studied. For a successful economic ship routing system, an efficient algorithm is needed to search an optimal geographical path, and most of the previous systems were approaching to that problem through a minimal static-cost path search algorithm based on the Dijkstra algorithm. To apply that kind of search algorithm, the cost of every edge assigned with the estimated fuel consumption should be constant. However, that assumption is not practical at all considering that the actual fuel consumption is determined by the weather condition when the ship will pass the edge. To overcome such a limitation, we propose a new optimal ship routing system based on a minimal dynamic-cost path search algorithm by properly modifying the Dijkstra algorithm. In addition, we propose a method which efficiently reduces the search space by using the $A^*$ algorithm to decrease the running time. We compared our system with the shortest path-based sailing method over ten testing routes and observed that the former reduced the estimated fuel consumption than the latter by 2.36% on average and the maximum 4.82% with little difference of estimated time of arrival.

• Korean Journal of Computational Design and Engineering
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• v.17 no.2
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• pp.71-78
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• 2012

Recently, the ratio of fuel cost to the operational cost of a ship is increasing according to the increase of the international oil price. Thus, many studies are being made to reduce the cost; for example, a method for acquiring the sea state information, a method for estimating fuel consumption, a method for determining the ship's optimal route, and so on. However, these studies were not incorporated together and being independently made in different fields. In this study, by improving and incorporating such studies, a method for determining a ship economic route based on the acquisition of the sea state and estimation of fuel consumption was proposed. To evaluate the applicability of the proposed method, it was applied to an optimal routing problem of the ocean area including many islands. The result shows that the proposed method can yield the economic route minimizing fuel consumption.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2015.10a
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• pp.155-156
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• 2015

최근 선박의 연료유 절감 및 경제운항에 대한 관심이 높아지면서 조선소를 중심으로 운항정보의 활용과 관련된 다수의 프로젝트가 진행되고 있으며 선박 설계, 기상예보 등을 통합한 다양한 시스템이 개발되는 등 선박의 최적운항지원 솔루션 시장이 빠르게 성장하고 있다. 하지만 현재 시장을 주도하고 있는 솔루션들은 설계정보를 중심으로 개발되어 선박을 운영하는 해운선사에서 요구하고 있는 성능기준을 만족하지 못하는 단점이 있다. 따라서 본 연구에서는 운영단계에서 축적되는 운항데이터와 해운선사의 경험과 노하우에 대한 정보가 반영된 경제운항 알고리즘을 개발하기 위한 현황 분석을 수행하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2014.11a
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• pp.821-824
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• 2014

선박경제운항이란 예보된 기상정보를 활용하여 연료소모량을 최소화하도록 선박을 운항하는 것으로서 최근 다양한 방법론이 연구되고 있다. 성공적인 경제운항시스템을 구현하기 위해서는 기상을 고려하여 지리적 운항경로를 바꾸거나 적절하게 엔진 출력을 조절하는 방법이 필요하다. 그러나 항해 시각에 따라 연료소모량이 변하는 동적 비용 문제임을 고려할 때 지리적 운항 경로의 결정은 최적의 해를 찾기가 어렵다. 이에 이 논문에서는 매우 많은 지리적 후보 경로들 중에서 우수한 품질의 해를 효과적으로 탐색하기 위한 진화전략 기반 경로탐색 알고리즘을 제안하였다. 제안된 방법을 5개 노선에 대해 실험한 결과 최단거리 운항 방법에 비해 운항소요시간은 거의 차이가 없으면서도 연료소모량을 평균 1.41%, 최대 1.45% 개선시킬 수 있었다.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.04a
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• pp.1064-1067
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• 2011

선박경제운항이란 파도와 바람과 같은 해양 기상정보 예측을 바탕으로 선박의 운항방법에 따른 연료 소모량과 운항시간을 예상해보고, 가장 경제적인 운항을 하는 것을 말한다. 본 논문에서는 실용화할 수 있는 범용의 경제운항시스템 개발에 중점을 두었다. 기존의 시스템들을 살펴보면 임의의 정해진 경로를 대상으로 실험하는 경우가 많은데, 이를 개선하여 임의의 출발점과 도착점이 주어지면 A*알고리즘을 통해서 지리상 최단경로를 찾아내도록 하여 시스템을 자동화하였으며 적용범위를 세계 전역으로 확대 하였다. 그리고 기존의 엔진출력을 고정하거나 속력을 일정하게 운항한다는 가정에서 벗어나서 엔진출력을 탐색하여 보다 효율적인 운항 솔루션을 찾아내도록 하였다. 그리고 사용측면에서는 운항사들에게 보다 효용성 높은 시스템이 되기 위해서, 일방적인 권고보다는 연료소모량과 운항시간 별로 다양한 솔루션들을 제공하여 운항사의 판단을 존중함과 동시에 운항보조시스템으로서의 역할에 충실할 수 있도록 하였다.