基于分级多目标决策的干线公交速度引导模型

为解决干线公交速度引导存在多要素关联约束强，全局效果差的问题，本文提出基于分级多目标决策的干线公交速度引导模型。基于公交线路运行特性的全局优化指标优势分析，设计以公交线路综合准点率为主，交叉口停车次数和分段引导速度均衡为辅的线路全局优化目标体系，并考虑多目标间的关联约束和优先控制差异，构建基于拉格朗日乘子法和遗传算法分层组合的干线公交速度引导分级多目标递阶决策模型；最后，通过实际场景测试，验证模型的有效性。测试结果表明：模型能够克服非全局指标优化的局部最优问题，将全线路各班次综合准点率和交叉口停车次数由非全局指标的69.67%和2.37次 ⋅ 班-1 提升到90.53%和1.23次 ⋅ 班-1；并且综合准点率比全局多目标加权方法提升8.65%，能够较好保障综合准点率目标的优先性，有效提升干线公交的通行效率和服务可靠性。

Hierarchical Multi-objective Model for Arterial Dedicated Bus Speed Optimization

In order to solve the problems of strong multi-factor linkage constraints and poor overall effect in arterial bus speed guidance, this paper proposes a hierarchical multi-objective speed guidance optimization model. A multiobjective optimization framework is designed to maximize the punctuality rate as the first-priority objective while the number of stops at intersections and the consistency of speed taking as the secondary objectives. With the associated constraints and priority among the multiple objectives, a hierarchical multi- objective decision- making approach is constructed by a combination of the Lagrangian multiplier method and genetic algorithm. Finally, an experiment based on actual scenarios is adopted to verify the effectiveness of the proposed model. The experiment results show that the model can guarantee the improvement of multiple performance indexes. It increases the overall punctuality rate from 69.67% to 90.53% and decreases the number of stops at intersections from 2.37 to 1.23 for each bus. Compared with the non-hierarchical multi-objective optimization method, the overall punctuality rate is improved by 8.65% in this hierarchical optimization method. The hierarchical optimization method provides the priority of the overall punctuality rate, and effectively improve the traffic efficiency and service reliability of dedicated buses.