Parallel ACO with a Ring Neighborhood for Dynamic TSP
This work addresses dynamic routing challenges for logistics and transportation, but it appears incremental as it builds on existing ant colony optimization methods.
The paper tackles the dynamic traveling salesman problem where distances between cities change over time, introducing a parallel ant colony optimization technique that successfully tested on large datasets.
The current paper introduces a new parallel computing technique based on ant colony optimization for a dynamic routing problem. In the dynamic traveling salesman problem the distances between cities as travel times are no longer fixed. The new technique uses a parallel model for a problem variant that allows a slight movement of nodes within their Neighborhoods. The algorithm is tested with success on several large data sets.