Performance Assessment of Algorithms for Ship Routing through AnyLogic Simulations

With constant improvement in intelligent technolo- gies across domains, improving intelligence in the maritime sector is very important. Optimal routing of ships in the vast ocean is a tedious task. Unmanned ships need a strong route planning system for easy operation on the field. The proposed work compares various shortest-path algorithms to find the optimal route between the source and the destination, based on cost. The algorithms implemented for the study are D-star, Delta Stepping, Theta-star, and AO-star. The practical implementation of the simulation has been performed using the Anylogic platform and implemented using the Python programming language. The time complexities of each algorithm have also been taken into account. From this, it has been analyzed that though the Theta-star algorithm seems to be efficient in terms of execution time with an average time 0.946 seconds, of the test cases chosen, the Delta Stepping algorithm proves to be more efficient as compared to the other algorithms taken for a larger sample size of scenarios of 0.97 seconds. On the other hand, the AO-star algorithm is found to be the least efficient algorithm for ship routing applications in terms of execution time with an average of 1.093 seconds.