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

fYear

2011

fDate

21-23 Oct. 2011

Firstpage

496

Lastpage

498

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;

fLanguage

English

Publisher

ieee

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

Type

conf

DOI

10.1109/ICCPS.2011.6092249

Filename

6092249