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GPU-Accelerated Tabu Search and Large Neighborhood Search to Solve Vehicle Routing Problem with Time Windows
Minhao Liu , WalmartLabs | Deyi Zhang, Walmart Labs
Learn various metaheuristic optimization algorithms to solve large-scale vehicle routing problems with time windows with GPU programming. We'll introduce a Tabu Search algorithm designed to exploit the parallelism in neighborhood search and its OpenACC-based implementation that applies deep-copy and manages complex data types. Then we'll introduce an Adaptive Large Neighborhood Search algorithm in which various combinations of destroy-and-repair heuristics are adaptively applied during the optimization process for the exploration of a substantially wider neighborhood of the solution space. We'll also describe the ALNS implementation using CUDA C and its running test on an NVIDIA DGX Station.