An improved parallel block coordinate descent method for the distributed computing of traffic assignment problem

Abstract

An improved parallel block coordinate descent (iPBCD) algorithm for solving the user equilibrium traffic assignment problem is proposed. The iPBCD algorithm is developed based on the parallel block coordinate descent algorithm (PBCD). The hybrid flow update policy is investigated to enhance the robustness and performance of the PBCD algorithm. Two update order rules, namely a cyclic rule and a greedy rule are compared for block indices. Then, the block size is optimized using a sensitivity analysis test. Finally, five index-grouping rules are tested for comparative purposes. Numerical experiments indicate that index-grouping rules have a significant influence on convergence: the information-based drop-out rule performs better in terms of convergence and efficiency.

KEYWORDS:

• Parallel computing
• block coordinate descent
• index-grouping rule
• user equilibrium
• gradient projection

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This research was supported by the National Key Research and Development Program of China (No. 2018YFB1600900) and the MOE (Ministry of Education in China) Project of Humanities and Social Sciences (Project No. 20YJAZH083).