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An enhanced parallel block coordinate descent algorithm with shared memory for solving large-scale user equilibrium problems
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DOI：10.1016/j.tre.2025.104377.png)
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Abstract
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• OpenMP-based parallelization of the PBCD algorithm to leverage shared memory parallelism efficiently. • Design of thread-private data structures to resolve data race issues in parallel computation. • Proposal of the Dynamic Block Reduction (DBR) method to adaptively adjust the parallel level during iterations. • Two schemes for DBR parameter selection: fixed parameters and self-adaptive parameters using the Armijo Rule. • Evaluation of a practical parallel computing framework, highlighting its substantial reduction in computation time and enhancement of performance in real-world, large-scale transportation networks.
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8.8
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