Abstract
The development of social economy has put forward higher and higher requirements for transportation, and the construction of transportation infrastructure has entered an important stage of rapid development. It is necessary to expand the network scale, improve the network level, and more importantly, accelerate the improvement of the network structure. Transportation network design is the most important issue in transportation planning, and it is also a hot issue in the field of transportation research. Traditional transportation network design usually ignores the uncertainty of transportation demand, which will bring risks to decision-making. When the expected traffic volume exceeds the capacity of the road network, how to choose an economical and reasonable expansion and optimization method to increase the capacity of the road network is an important issue that the transportation department needs to face. The purpose of this article is to use network capacity optimization algorithms to plan transportation. An optimization model for traffic network expansion is established, and a shortest path reconstruction and expansion cost progressive iterative algorithm is designed. The validity of the model and its algorithm can be verified, which can provide a reference for solving the optimization problem of transportation capacity expansion. Based on the maximum flow theory, a method for determining the capacity limit of the road network is proposed. In order to minimize transportation costs, a capacity optimization model is established and corresponding algorithms are designed. The experimental results show that the model and algorithm studied in this paper are effective, and the capacity expansion part of the capacity expansion optimization scheme is basically consistent with the capacity limitation part of the road network.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Fu, Z., Yang, Y., Gao, X., et al.: An optimization algorithm for multi-characteristics road network matching. Acta Geodaet. Cartographica Sin. 45(5), 608–615 (2016)
Gralla, E., Goentzel, J.: Humanitarian transportation planning: evaluation of practice-based heuristics and recommendations for improvement. Eur. J. Oper. Res. 269, 436–450 (2018)
Yao, Z., Jiang, Y., Bin, Z., et al.: A traffic signal timing rolling optimization algorithm based on dynamic programming. Gonglu Jiaotong Keji/J. Highw. Transp. Res. Dev. 36(1), 124–130 (2019)
Chau, C.K., Elbassioni, K., Tseng, C.M.: Drive mode optimization and path planning for plug-in hybrid electric vehicles. IEEE Trans. Intell. Transp. Syst. 18, 3421–3432 (2016)
Lim, W., Lee, S., Sunwoo, M., et al.: Hierarchical trajectory planning of an autonomous car based on the integration of a sampling and an optimization method. IEEE Trans. Intell. Transp. Syst. 19(2), 1–14 (2018)
Li, M., Wang, X., Sun, Q., et al.: Research on allocation strategies of multimodal transportation for emergency resources based on robust optimization. J. Chin. Railw. Soc. 39(7), 1–9 (2017)
Zhang, W., Wei, D.: Prediction for network traffic of radial basis function neural network model based on improved particle swarm optimization algorithm. Neural Comput. Appl. 29(1), 1–10 (2016)
Xu, C., Li, K.: Cooperative test scheduling of 3D NoC under multiple constraints based on the particle swarm optimization algorithm. Chin. J. Sci. Instrum. 38(3), 765–772 (2017)
Zhao, P., Feng, L., Yu, P., et al.: A fairness resource allocation algorithm for coverage and capacity optimization in wireless self-organized network. Chin. Commun. 15(11), 10–24 (2018)
Sedghi, M., Ahmadian, A., Aliakbar-Golkar, M.: Assessment of optimization algorithms capability in distribution network planning: review, comparison and modification techniques. Renew. Sustain. Energy Rev. 66, 415–434 (2016)
Ma, L., Hu, S., Qiu, M., et al.: Energy consumption optimization of high sulfur natural gas purification plant based on back propagation neural network and genetic algorithms. Energy Procedia 105, 5166–5171 (2017)
Chen, D., Hu, M., Zhang, H., et al.: A network based dynamic air traffic flow model for en route airspace system traffic flow optimization. Transp. Res. Part E Logist. Transp. Rev. 106, 1–19 (2017)
Cui, K., Lang, L., Chen, M., et al.: Research on WSN notes fault localization based on cluster localization in power network. Chin. J. Sens. Actuators 30(1), 146–151 (2017)
Yao, X.W., Wang, W.L., Yang, S.H.: Joint parameter optimization for perpetual Nanonetworks and maximum network capacity. IEEE Trans. Mol. Biol. Multi-Scale Commun. 1(4), 321–330 (2017)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Han, P. (2020). Transportation and Planning Based on Network Expansion Optimization Algorithm. In: Xu, Z., Parizi, R., Hammoudeh, M., Loyola-González, O. (eds) Cyber Security Intelligence and Analytics. CSIA 2020. Advances in Intelligent Systems and Computing, vol 1146. Springer, Cham. https://doi.org/10.1007/978-3-030-43306-2_16
Download citation
DOI: https://doi.org/10.1007/978-3-030-43306-2_16
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-43305-5
Online ISBN: 978-3-030-43306-2
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)