@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)} }