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Series queuing network scheduling approach to co-scheduling model of three Gorges-Gezhou dam
Authors:Xiaoping Wang  Huan Qi  Henghui Xiao  Xiaopan Zhang  Yang Hu  Xiaojian Feng
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
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.
Keywords:Co-scheduling  intelligent transportation systems(ITS)  mathematics model  series queuing network(SQN)  three Gorges-Gezhou Dam  
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