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Wyszukujesz frazę "route optimization algorithm" wg kryterium: Temat


Wyświetlanie 1-2 z 2
Tytuł:
Multi-Objective Optimization of Motor Vessel Route
Autorzy:
Marie, S.
Courteille, E.
Powiązania:
https://bibliotekanauki.pl/articles/117604.pdf
Data publikacji:
2009
Wydawca:
Uniwersytet Morski w Gdyni. Wydział Nawigacyjny
Tematy:
route planning
Optimization of Vessel Route
multi-objective optimization
Motor Vessel
Optimal Route
Multi-Objective Genetic Algorithm (MOGA)
Bézier Curve
MATLAB
Opis:
This paper presents an original method that allows computation of the optimal route of a motor vessel by minimizing its fuel consumption. The proposed method is based on a new and efficient meshing procedure that is used to define a set of possible routes. A consumption prediction tool has been developed in order to estimate the fuel consumption along a given trajectory. The consumption model involves the effects of the meteorological conditions, the shape of the hull and the power train characteristics. Pareto-optimization with a Multi-Objective Genetic Algorithm (MOGA) is taken as a framework for the definition and the solution of the multi-objective optimization problem addressed. The final goal of this study is to provide a decision helping tool giving the route that minimizes the fuel consumption in a limited or optimum time.
Źródło:
TransNav : International Journal on Marine Navigation and Safety of Sea Transportation; 2009, 3, 2; 133-141
2083-6473
2083-6481
Pojawia się w:
TransNav : International Journal on Marine Navigation and Safety of Sea Transportation
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Multi-criteria ACO-based algorithm for ship’s trajectory planning
Autorzy:
Lazarowska, A.
Powiązania:
https://bibliotekanauki.pl/articles/116548.pdf
Data publikacji:
2017
Wydawca:
Uniwersytet Morski w Gdyni. Wydział Nawigacyjny
Tematy:
colregs
ships manoeuvering
Ant Colony Optimization (ACO)
ship’s trajectory planning
route planning
multi-criteria ACO-based algorithm
guidance
navigation and control (GNC)
ARPA
Opis:
The paper presents a new approach for solving a path planning problem for ships in the environment with static and dynamic obstacles. The algorithm utilizes a heuristic method, classified to the group of Swarm Intelligence approaches, called the Ant Colony Optimization. The method is inspired by a collective behaviour of ant colonies. A group of agents - artificial ants searches through the solution space in order to find a safe, optimal trajectory for a ship. The problem is considered as a multi-criteria optimization task. The criteria taken into account during problem solving are: path safety, path length, the International Regulations for Preventing Collisions at Sea (COLREGs) compliance and path smoothness. The paper includes the description of the new multi-criteria ACO-based algorithm along with the presentation and discussion of simulation tests results.
Źródło:
TransNav : International Journal on Marine Navigation and Safety of Sea Transportation; 2017, 11, 1; 31-36
2083-6473
2083-6481
Pojawia się w:
TransNav : International Journal on Marine Navigation and Safety of Sea Transportation
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-2 z 2

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