Vehicle scheduling model considering individual driving speed deviation

ZHANG Na; YANG Qi; HU Fei-hu; JIANG Xin-yu; LIU Yong-xiong

doi:10.19818/j.cnki.1671-1637.2020.05.015

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ZHANG Na, YANG Qi, HU Fei-hu, JIANG Xin-yu, LIU Yong-xiong. Vehicle scheduling model considering individual driving speed deviation[J]. Journal of Traffic and Transportation Engineering, 2020, 20(5): 187-197. doi: 10.19818/j.cnki.1671-1637.2020.05.015

Citation:

ZHANG Na, YANG Qi, HU Fei-hu, JIANG Xin-yu, LIU Yong-xiong. Vehicle scheduling model considering individual driving speed deviation[J]. Journal of Traffic and Transportation Engineering, 2020, 20(5): 187-197. doi: 10.19818/j.cnki.1671-1637.2020.05.015

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Vehicle scheduling model considering individual driving speed deviation

doi: 10.19818/j.cnki.1671-1637.2020.05.015

ZHANG Na^{1, 2, 3
,},
YANG Qi^4
,,
HU Fei-hu^{5
,
,},
JIANG Xin-yu⁵,
LIU Yong-xiong⁶

1.
College of Transportation Engineering, Chang'an University, Xi'an 710064, Shaanxi, China
2.
School of Humanities, Chang'an University, Xi'an 710064, Shaanxi, China
3.
Moody College of Communication, The University of Texas at Austin, Austin TX78705, Texas, USA
4.
School of Economics and Management, Chang'an University, Xi'an 710064, Shaanxi, China
5.
School of Electric Engineering, Xi'an Jiaotong University, Xi'an 710049, Shaanxi, China
6.
School of Information Engineering, Chang'an University, Xi'an 710064, Shaanxi, China

Funds:

National Natural Science Foundation of China 71732006

National Natural Science Foundation of China 61174154

Social Science Foundation of Shaanxi Province 2019S032

Fundamental Research Funds for the Central Universities 310833160212

Sichuan Major Project of Science and Technology Achievements Transter Demonstration 21ZHSF0055

More Information

Author Bio:
ZHANG Na(1981-), female, associate professor, doctoral student, zhangna@chd.edu.cn

YANG Qi(1963-), male, professor, PhD, yangqi@chd.edu.cn

HU Fei-hu(1972-), male, associate professor, PhD, hufeihu@mail.xjtu.edu.cn
Received Date: 2020-04-25
Publish Date: 2020-10-25

Abstract

Abstract

In view of driving speed deviation, a vehicle scheduling model was established for multi-drivers, multi-vehicles, multi-materials, multi-depots, and multi-demands targeting at the shortest overall transportation time, the lowest overall transportation cost and the least multi-objective overall transportation time and cost, respectively. The effects of individual driving speed deviation on the above targets were studied. The driver parameters were input into the gene coding of the genetic algorithm. The constraints of driver uniqueness, initial location, and the supply and demand quantities of materials were established to ensure that the distribution scheme of drivers in each gene was feasible and the material transportation did not exceed the total supply and demand. A genetic algorithm was applied to solve the vehicle scheduling schemes for each target with and without driving speed deviation under the condition of randomly assigned drivers. Calculation result shows that the optimized scheduling schemes satisfy all the constraints in the model. For the three optimal schemes, the driver assignments are different, indicating that the target function is affected by the driving speed deviation. The dispatching results of each target with driving speed deviation are superior to those without driving speed deviation. The difference ratios of the three objective functions are 3.5%, 2.96% and 1.13%, respectively, which shows that the driving speed deviation has a certain influence on the solving quality. The target scheduling results of the driver's random assignment are inferior to the corresponding optimal results. The different ratios of the three objective functions are 3.91%, 2.47% and 1.98%, respectively, showing that the dispatching efficiency is affected by the driving speed deviation, and optimizing the driver allocation scheme can reduce the overall transport time and cost. Analysis result shows that the vehicle scheduling scheme, which is more in line with the scheduling target, closer to reality, and more economical and time-saving, can be obtained by allocating drivers reasonably according to the specific dispatching target.
- vehicle scheduling,
- scheduling scheme,
- genetic algorithm,
- driving speed deviation,
- driver assignment

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References(35)

References

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Vehicle scheduling model considering individual driving speed deviation

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