Abstract
The Yangtze River is the largest river in China, and the navigable resources are abundant, with the development of the economic belt along the Yangtze River, a large number of ships have been backlogged, which result in the Yangtze Gorges ship locks navigable capacity insufficient contradictions obviously and increasingly. In case of special weather or ship locks maintenance, ships will pile up. Based on the analysis of influencing factors of the ship lock navigable capacity, this paper draws the conclusion that the maximum value problem about the lockage tonnage every time is actually a problem of the ship lock arrangement optimization, establishes the Multi-Colony Ant Algorithm for the ship lock arrangement optimization, furtherly designs and implements the corresponding algorithm, and tests the algorithm through two examples. The experimental results show that the Multi-Colony Ant Algorithm is effective to the arrangement optimization of the Yangtze Gorges ship lock, it can improve the practical navigable capacity of the Yangtze Gorges ship lock.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Zeng, F.F.: Packing Problem Research of Navigable Co-scheduling System for Ship-lift at Three Georges Project and Lock. Central South University of Forestry and Technology, Changsha (2016)
Deng, W.F.: Cascade hub Research of Navigable Co-scheduling System for Ship-lift at Three Georges Project and Lock. Central South University of Forestry and Technology, Changsha (2017)
Zhou, C.F.: Design of ship arrangement algorithm for an expanded non-rectangular lock chamber. J. Dalian Maritime Univ. 43(2), 27–32 (2017)
Zhang, Y.F.: Research on traffic flow prediction and ship lock scheduling model of in-land river. Zhejiang Gongshang University, Hangzhou (2018)
Liu, Y.F.: The Optimization Research of ship lock operation-Verified by Qing-yuan Water Conservancy Lock. South China University of Technology, Guangzhou (2016)
Liu, R.F., Qin, F.S., Zhai, Y.T., Wang, L.F.: Ship lock arrangement in yangtze gorges based on simulated annealing algorithm. Comput. Modernization (11), 65–67 (2013)
Liu, W.F.: Application of greedy algorithm in the arranging of lock chamber. Com-put. Knowl. Technol. 7(10), 2417–2418 (2011)
Liao, P.F., Zhang, W.S.: Analytical model for average lockage tonnage of waterway lock. J. Southeast Univ. (Nat. Sci. Ed.) 40(1), 207–212 (2010)
Sun, B.F., Qi, H.S., Zhang, X.T., Cai, X.F.: Dimensionality reduction quickly arranging algorithm of lock chambers in co-scheduling of yangtze gorges dam and gezhouba dam system. Comput. Technol. Dev. 16(12), 19–21 (2006)
Dorigo, M.F., Caro, G.D.S., Gambardella, L.M.T.: Ant algorithms for discrete optimization. Artif. Life 5(2), 137–172 (1999)
Melo, F.L., Pereira, S.F., Costa, T.E.: MC-ANT: a multi-colony ant algorithm. Artif. Evol. LNCS 5975, 25–36 (2010)
Aljanaby, A.F., Ku-Mahamud, K.R.S., Norwawi, N.M.T.: Interacted multiple ant colonies optimization approach to enhance the performance of ant colony optimization algorithms. Comput. Inf. Sci. 3(1), 29–34 (2010)
Acknowledgment
Authors thank Leonor Melo, Aljanaby A and Zeng Feifan et al. for the related research on the Multi-Colony Ant Algorithm and the ship lock arrangement.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Liu, R., Lin, Q., Wang, L., Li, L., Wang, C. (2021). Multi-Colony Ant Algorithm Applied to the Yangtze Gorges Ship Lock Arrangement Optimization. In: Tavana, M., Nedjah, N., Alhajj, R. (eds) Emerging Trends in Intelligent and Interactive Systems and Applications. IISA 2020. Advances in Intelligent Systems and Computing, vol 1304. Springer, Cham. https://doi.org/10.1007/978-3-030-63784-2_112
Download citation
DOI: https://doi.org/10.1007/978-3-030-63784-2_112
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-63783-5
Online ISBN: 978-3-030-63784-2
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)