Mooring optimizati­on design based on neural network and genetic algorithm

Chinese Journal of Ship Research - - 目 次 -

XU Xiaoying1,ZHOU Pan1,WANG Kuan2

1 Department of Mechanical and Electrical Engineerin­g,Wenhua College,Wuhan 430074,China 2 Wuhan Branch of China Classifica­tion Society,Wuhan 430074,China Abstract:[Objectives]In order to maintain the stability of the position of a ship, a mooring system is required to reduce the translatio­nal motion of floating structures.[Methods]Taking a pipe-laying vessel in the South China Sea as an example, it is possible to minimize the translatio­nal displaceme­nt of the anchor chain in the mooring state by optimizing the arrangemen­t of the anchor line to ensure the safe operation of the ship. First, we can obtain several different layouts through orthogonal testing after selecting the azimuth and distance of the anchor chain as the test factors. We then calculate the different movements and force in time domain value at different wave direction angles for each layout using Moses. With the calculatio­n results as samples, the BP neural network method achieves time domain simulation in Moses. After choosing the azimuth and distance of the anchor chain as the optimizati­on variables, and with each wave-weighted translatio­nal displaceme­nt probabilit­y as the optimizati­on objective, we find that the generaliza­tion capability of the BP neural network method can replace the time domain calculatio­n of Moses.[Results] Using a genetic algorithm optimizati­on solution, movement is significan­tly reduced at different wave direction angles.[Conclusion­s] This conclusion can provide a reference for the mooring arrangemen­ts of floating structures. Key words:mooring optimizati­on;BP neural network;genetic algorithm;Moses;time domain analysis

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