Series queuing network scheduling approach to co-scheduling model of three Gorges-Gezhou dam |
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Authors: | Xiaoping Wang Huan Qi Henghui Xiao Xiaopan Zhang Yang Hu Xiaojian Feng |
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Institution: | (1) International Institute for Geo-Information Science and Earth Observation (ITC), P.O. Box 6, 7500 AA Enschede, The Netherlands;(2) Present address: International Livestock Research Institute (ILRI), P.O. Box 30709, Nairobi, Kenya;(3) Department of Geography, University of Alabama, Tuscaloosa, AL 35487-0322, USA;(4) School of Resources and Environmental Science, Wuhan University, 129 Luoyu Road, 430079 Wuhan, People’s Republic of China;(5) Resource Ecology Group, Wageningen University, Droevendaalsesteeg 3a, 6708 PB Wageningen, The Netherlands;(6) International Crane Foundation, P.O. Box 447, Baraboo, WI 53913, USA;(7) State Key Laboratory of Estuarine and Coastal Research, East China Normal University, North Zhongshan Road 3663, Shanghai, 200062, China;(8) SERTIT, Strasbourg University, Pole API, Boulevard Sebastien Brant, BP 10413, 67412 Illkirch, France |
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Abstract: | This paper provides a mathematical model for Three Gorges-Gezhou dam co-scheduling problem, based on full analysis of Three
Gorges-Gezhou dam’s actual needs, to maximize the total throughput of Three Gorges-Gezhou dam and the utilization ratio of
shiplock area and minimize the total navigation shiplock waiting time under multiple constraints. This paper proposes a series
queuing network (SQN) scheduling algorithm to divide the total ships that intend to pass through the shiplocks into four queues
and calculate dynamically the weight of priority for each ship. The SQN scheduling algorithm schedules ships according to
their priority weights which is determined by the characteristics of each ship, such as length, width, affiliation, waiting
time, and so on. In the process, the operation conditions of Gezhou dam related to the navigable shiplocks and the task balancing
among different shiplocks also should be considered. The SQN algorithm schedules ships circularly and optimizes the results
step by step. Real operation data from our project shows that our SQN scheduling algorithm outperforms the traditional manual
scheduling in which the less computational time is taken, the area utilization ratio of the five shiplocks is increased, the
waiting time of high-prioritized ships is shorten, and a better balanced and alternating run-mode is provided for the three
shiplocks in the Gezhou dam. |
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Keywords: | Co-scheduling intelligent transportation systems(ITS) mathematics model series queuing network(SQN) three Gorges-Gezhou Dam |
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