The Capacitated Arc Routing Problem (CARP) is an NP-hard optimization problem that has been investigated for decades.Heuristic search methods are commonly used to solve it.However, given a CARP instance, most heuristic search algorithms require plenty of time to Samsung RS52N3313WW No Frost Side-by-side Fridge Freezer With Non-pl iteratively search for the solution from scratch, and hence may be impractical for emerging applications that need a solution to be obtained in a very short time period.
In this work, a novel approach to efficiently solve CARP is presented.The proposed approach replaces the heuristic search process with the inference phase of a trained Deep Neural Network (DNN), which is trained to take a CARP instance as the input and outputs a solution to the instance.In this way, CARP could be solved by a direct mapping rather than by iterative search, and hence could be more efficient and more easily accelerated by Furniture-Setup the use of GPUs.
Empirical study shows that the DNN-based solver can achieve significant speed-up with minor performance loss, and up to hundreds of times acceleration in extreme cases.