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.

提出一种解决用户均衡流量分配问题的改进并行块坐标下降（iPBCD）算法。iPBCD 算法是基于并行块坐标下降算法 (PBCD) 开发的。研究了混合流更新策略以增强 PBCD 算法的鲁棒性和性能。比较两个更新顺序规则，即循环规则和贪婪规则以用于块索引。然后，使用敏感性分析测试优化块大小。最后，为了比较的目的，测试了五个指数分组规则。数值实验表明，索引分组规则对收敛性有显着影响：基于信息的 drop-out 规则在收敛性和效率方面表现更好。