Parallel ACO with a Ring Neighborhood for Dynamic TSP
Camelia-M. Pintea, Gloria Cerasela Crisan, Mihai Manea
TL;DR
This paper presents a parallel ant colony optimization method tailored for the dynamic traveling salesman problem, where city locations can shift slightly, demonstrating effectiveness on large datasets.
Contribution
It introduces a novel parallel ACO approach incorporating a ring neighborhood for dynamic TSP, enhancing adaptability to changing city positions.
Findings
Successfully tested on large datasets
Effective in dynamic routing scenarios
Improves solution quality in dynamic TSP
Abstract
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.
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