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실시간 적응 A* 알고리즘과 기하학 프로그래밍을 이용한 선박 최적항로의 2단계 생성기법 연구

Two-Phase Approach to Optimal Weather Routing Using Real-Time Adaptive A* Algorithm and Geometric Programming

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초록

This paper proposes a new approach for solving the weather routing problem by dividing it into two phases with the goal of fuel saving. The problem is to decide two optimal variables: the heading angle and speed of the ship under several constraints. In the first phase, the optimal route is obtained using the Real-Time Adaptive A* algorithm with a fixed ship speed. In other words, only the heading angle is decided. The second phase is the speed scheduling phase. In this phase, the original problem, which is a nonlinear optimization problem, is converted into a geometric programming problem. By solving this geometric programming problem, which is a convex optimization problem, we can obtain an optimal speed scheduling solution very efficiently. A simple case of numerical simulation is conducted in order to validate the proposed method, and the results show that the proposed method can save fuel compared to a constant engine output voyage and constant speed voyage.

Abstract

This paper proposes a new approach for solving the weather routing problem by dividing it into two phases with the goal of fuel saving. The problem is to decide two optimal variables: the heading angle and speed of the ship under several constraints. In the first phase, the optimal route is obtained using the Real-Time Adaptive A* algorithm with a fixed ship speed. In other words, only the heading angle is decided. The second phase is the speed scheduling phase. In this phase, the original problem, which is a nonlinear optimization problem, is converted into a geometric programming problem. By solving this geometric programming problem, which is a convex optimization problem, we can obtain an optimal speed scheduling solution very efficiently. A simple case of numerical simulation is conducted in order to validate the proposed method, and the results show that the proposed method can save fuel compared to a constant engine output voyage and constant speed voyage.

참고문헌 (9)

  1. Boyd, S., "A tutorial on geometric programming", Optimization Engineering, 8(1), pp.67~127 (2007)
  2. He-ping, H., "The Development Trend of Green Ship Building Technology", Guangdong Shipbuilding, 3, pp.002~ (2007)
  3. Hinnenthal, J., "Robust Pareto-optimum Routing of Ships utilising Deterministic and Ensemble Weather Forecasts", Ships and Offshore Structure, 5(2), pp.105~114 (2010)
  4. Circ. 1228), "Revised Guidance to the Master for Avoiding Dangerous Situations in Adverse Weather and Sea Conditions (MSC", pp.2007, International Maritime Organization(IMO)
  5. Koenig, S., "Real-time Adaptive A*", Proceedings of the Fifth International Joint Conference on Autonomous Agents and Multiagent Systems, pp.281~288 (2006)
  6. 노명일, "Determination of an economical shipping route considering the effects of sea state for lower fuel consumption", International Journal of Naval Architecture and Ocean Engineering, 5(2), pp.246~262 (2013), 대한조선학회
  7. Russell, S. J., "Artificial Intelligence : a Modern Approach(Vol. 2)" (1995), Prentice Hall
  8. Shao, W., "Development of a Novel Forward Dynamic Programming Method for Weather Routing", Journal of Marine Science and Technology, 17(2), pp.239~251 (2012)
  9. Townsin, R. L., "Estimating the Influence of Weather on Ship Performance", Royal Institute of Naval Architecture Trans, 134(B), pp.191~210 (1993)

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