Title :
Production model design and optimization of TSHD based on genetic algorithm
Author :
Wei, Li ; Feng, Lin ; Shuo, Zhang
Author_Institution :
CCCC Dredging Key-Lab., Shanghai Waterway Eng. Design & Consulting Co. Ltd., Shanghai, China
Abstract :
The ultimate goal for a Trailing Suction Hopper Dredger (TSHD) is maximizing the profit. The performance of the dredger is strongly influenced by the operator´s strategy and the soil properties. A decision support system can help the operator maximizing the performance by using models. In this paper, the optimization method which combined the Neural Network (NN) model with the genetic algorithm (GA) was proposed. By using the recorded process data from a dredger, the effectiveness of the model was calibrated. By means of comparison study, the production rate of the TSHD was increased.
Keywords :
decision support systems; genetic algorithms; neural nets; production engineering computing; ships; TSHD optimization; decision support system; genetic algorithm; neural network model; operator strategy; process data recording; production model design; soil property; trailing suction hopper dredger; Data models; Genetic algorithms; Optimization; Pressure measurement; Productivity; Sensors;
Conference_Titel :
Computational Problem-Solving (ICCP), 2011 International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4577-0602-8
Electronic_ISBN :
978-1-4577-0601-1
DOI :
10.1109/ICCPS.2011.6092249
