考虑公交与地铁换乘需求的公交时刻表优化

doi:10.13229/j.cnki.jdxbgxb.20230931

Abstract

Abstract:

An all-day bus schedule optimization method was proposed in consideration of passengers' demand between the bus and the metro. Firstly， with the goal of minimizing the cost of passenger waiting time and the operating costs of public transportation enterprises， an optimization model was constructed. Then， a genetic-simulated annealing hybrid algorithm was designed to solve the model. A case study of the upward direction of the No. 1 bus in Fuzhou was selected to verify the effectiveness and practicability of the proposed model and algorithm. After optimizing the schedule， the average waiting time cost of passengers in B-M mode， M-B mode， and non-transfer mode has been reduced by 19.30%. Public transportation enterprises' operating costs have increased by 4.95% due to increased bus departures， but the total system cost has decreased by 5.05%.

Key words: urban traffic, schedule optimization, genetic-simulated annealing hybrid algorithm, interchange needs, waiting time

CLC Number:

U491

Yuan-wen LAI,Yan-sheng CHEN,Shu-yi WANG,Yu-long ZHANG,Xin-yun ZHU. Bus schedule optimization considering bus and metro interchange needs[J].Journal of Jilin University(Engineering and Technology Edition), 2025, 55(6): 2030-2037.

Figures/Tables 9

Table 1

Test function properties"

测试函数	搜索范围	理论最优值	目标精度
$f 1 x$	（-10，10）	3 600	e^-5
$f 2 x$	（-10，10）	186.73	e^-5
$f 3 x$	（-10，10）	0	e^-5

Table 1

Fig.1

Table 2

Table 3

Table 4

Table 5

Model and algorithm parameters"

参数符号	参数属性	参数取值	参考文献
$h B, m i n$	公交最小发车间隔/min	5	—
$h B, m a x$	公交最大发车间隔/min	60	—
$U p$	公交线路单位里程的运营成本/（元·km^-1）	5.97	—
$K$	公交线路的最大发车次数/（次·h^-1）	12	—
$V p$	乘客的平均步行速度/（km·h^-1）	4.4	［17］
$U c$	乘客单位候车时间价值/（元·min^-1）	0.37	［18］
$P c$	交叉概率	0.8	［19］
$P m$	变异概率	0.01	［19］
$P$	种群规模	100	［19］
$G m a x$	最大进化次数	20	［19］
$α$	冷却系数	0.99	［20］

Table 5

Fig.2

Table 6

Table 7

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时段编号	时段	时长/min
1	5：00~7：00	120
2	7：00~9：00	120
3	9：00~12：00	180
4	12：00~14：00	120
5	14：00~17：00	180
6	17：00~19：00	120
7	19：00~21：00	120
8	21：00~23：00	120

时段编号	发车时刻	发车间隔/min
1	05：00；05：12；05：24；05：36；05：48；06：00；06：12；06：24；06：36；06：48；07：00	12
2	07：08；07：16；07：24；07：32；07：40；07：48；07：56；08：04；08：12；08：20；08：28；08：36；08：44；08：52；09：00	8
3	09：10；09：20；09：30；09：40；09：50；10：00；10：10；10：20；10：30；10：40；10：50；11：00；11：10；11：20；11：30；11：40；11：50；12：00	10
4	12：11；12：22；12：33；12：44；12：55；13：06；13：17；13：28；13：39；13：50	11
5	14：02；14：14；14：26；14：38；14：50；15：02；15：14；15：26；15：38；15：50；16：02；16：14；16：26；16：38；16：50	12
6	17：02；17：11；17：20；17：29；17：38；17：47；17：56；18：05；18：14；18：23；18：32；18：41；18：50；18：59	9
7	19：12；19：25；19：38；19：51；20：04；20：17；20：30；20：43；20：56	13
8	21：11；21：26；21：41；21：56；22：11；22：26；22：41；22：56	15

对比项	优化前	优化后	优化比例/%
发车次数/次	96	100	-4.17
B-M模式下的乘客候车时间成本/元	362.10	307.30	15.13
M-B模式下的乘客候车时间成本/元	710.20	539.60	24.02
非换乘模式下的乘客候车时间成本/元	3 511.50	2 852.60	18.76
公交企业运营成本/元	6 361.60	6 693.00	-4.95
系统总成本/元	10 945.40	10 392.50	5.05

Bus schedule optimization considering bus and metro interchange needs

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