The paper represents an algorithm for planning safe and optimal routes for transport facilities with unrestricted movement direction that travel within areas with obstacles. Paper explains the algorithm using a ship as an example of such a transport facility. This paper also provides a survey of several existing solutions for the problem. The method employs an evolutionary algorithm to plan several locally optimal routes and a parallel genetic algorithm to create the final route by optimising the abovementioned set of routes. The routes are optimized against the arrival time, assuming that the optimal route is the route with the lowermost arrival time. It is also possible to apply additional restriction to the routes.
Paper @cite_18 describes a dynamic programming method for plotting a route for a ship. In this case route is a sequence of tuples each of which describes engine power and ship's heading during voyage. This method requires hydrodynamic model of a ship for which a route is being planned and method's precision depends on the precision of the model. Moreover, this method assumes that an external optimization method is used to solve the dynamic programming problem.
@cite_18
2034412030 2100687146 2039870579 2888625733
This paper presents a novel forward dynamic programming method for weather routing to minimise ship fuel consumption during a voyage. Compared with traditional weather routing methods which only optimise the ship’s heading, while the engine power or propeller rotation speed is set as a constant throughout the voyage, this new method considers both the ship power settings and heading controls. A float state technique is used to reduce the iterations required during optimisation and thus save computation time. This new method could lead to quasi-global optimal routing in comparison with the traditional weather routing methods. A curve fitting algorithm for batch ship trajectory estimation that employs Bayesian statistical inference for non-parametric regression is presented. It assumes no knowledge about the ship motion model while only assuming standard ship maneuvers. The trajectory is thought to be well represented by a cubic spline with an unknown number of knots in two-dimensional Euclidean plane. The function estimate is determined from positional measurements which are assumed to be received in batches at irregular time intervals. As the measurements are often delivered by different sensors the measurement errors are assumed to be heteroscedastic and correlated. A fully Bayesian approach is adopted by defining the prior distributions on all unknown parameters: the spline coefficients as well as the number and the locations of knots. The quality of the estimator algorithm is evaluated statistically using several simulated scenarios. The results suggest that the algorithm represents efficient methodology for trajectory estimation in maritime surveillance, especially in the absence of prior knowledge of the motion model. © 1997-2012 IEEE. This paper presents a method for generating complex problems that allow multiple nonobvious solutions for the physical traveling salesman problem (PTSP). PTSP is a single-player game adaptation of the classical traveling salesman problem that makes use of a simple physics model: the player has to visit a number of waypoints as quickly as possible by navigating a ship in real time across an obstacle-filled 2-D map. The difficulty of this game depends on the distribution of waypoints and obstacles across the 2-D plane. Due to the physics of the game, the shortest route is not necessarily the fastest, as the ship's momentum makes it difficult to turn sharply at high speed. This paper proposes an evolutionary approach to obtaining maps where the optimal solution is not immediately obvious. In particular, any optimal route for these maps should differ distinctively from: 1) the optimal distance-based TSP route and 2) the route that corresponds to always approaching the nearest waypoint first. To achieve this, the evolutionary algorithm covariance matrix adaptation-evolutionary strategy (CMA-ES) is employed, where maps, indirectly represented as vectors of real numbers, are evolved to differentiate maximally between a game-playing agent that follows two or more different routes. The results presented in this paper show that CMA-ES is able to generate maps that fulfil the desired conditions. Abstract Weather ship routing has become a recognized measure to target safe, sustainable and economical ship activities. Academic research has focused the ship routing optimization through pathfinding algorithms which take into account the meteo-oceanographic forecasts (i.e. wind, waves or currents predictions). This contribution shows the results of the numerical simulations carried out during the development of a weather ship routing applied to a ferry service in the Mediterranean Sea: Barcelona – Palma de Mallorca. From a methodological point of view, the pathfinding A* algorithm is applied to optimize the travel time considering the wave action. Under severe weather conditions, a reduction of the 7 of the travel time is obtained comparing the optimized route and the minimum distance route. The results show also a non-significant correlation between the travel time reduction and wave height. In consequence the benefit of ship routing depends not only of the wave height but also in the spatial sequence of the storm.