@article{Lazarowska_2017,
	author = {Lazarowska, Agnieszka},
	title = {Multi-criteria ACO-based Algorithm for Ship's Trajectory Planning},
	journal = {TransNav, the International Journal on Marine Navigation and Safety of Sea Transportation},
	volume = {11},
	number = {1},
	pages = {31-36},
	year = {2017},
	url = {./Article_Multi-criteria_ACO-based_Algorithm_Lazarowska,41,695.html},
	abstract = {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.},
	doi = {10.12716/1001.11.01.02},
	issn = {2083-6473},
	publisher = {Gdynia Maritime University, Faculty of Navigation},
	keywords = {Colregs, ARPA, Route Planning, Ships Manoeuvering, Ant Colony Optimization (ACO), Ship's Tajectory Planning, Multi-Criteria ACO-Based Algorithm, Guidance, Navigation and Control (GNC)}
}