摘要
科学规划公交系统是解决城市交通拥挤问题的有效手段,公交网络设计问题更是公交体系规划的重点与难点。公交需求作为公交网络设计的输入条件,在现实中具有不确定性。鉴于此,假设不确定乘客需求具有随机特性,来研究随机需求下公交网络设计问题的优化方法。以乘客成本与运营成本最小化为优化目标,构建了多目标规划的期望值模型。将遗传算法与模拟退火算法相结合,设计了求解模型的遗传模拟退火算法。最后,通过算例验证了提出的模型与算法的有效性。
Scientific public transit system planning was the effective way to solve the problem of urban traffic congestion.Transit network design problem was the focus of public transit system planning.As the input of the transit network design,the transit demand was provided with uncertainty characteristics.With the assumption of uncertainty demand having stochastic characteristics,the optimization methodology of transit network design problem under stochastic demand was worked on.A multi-objective programming expected value model was proposed to minimize passenger cost and operation cost.Genetic algorithm was combined with simulated annealing algorithm to design the genetic simulated annealing algorithm for solution of the proposed model.At last,numerical examples are given to demonstrate the effectiveness of the proposed models and algorithms.
出处
《交通标准化》
2013年第17期22-25,共4页
Communications Standardization
关键词
公交网络
网络设计
随机需求
期望值模型
遗传模拟退火算法
transit network
network design
stochastic demand
expected value model
genetic-simulated annealing algorithm
