Optimization of warp-chine pentamaran configuration using Artificial Neural Network and Genetic Algorithm

Abstract

This study aims to find the optimal pentamaran configuration to reduce wave resistance and total resistance at various speeds. We evaluate the outrigger distance with a fixed warp-chine hull shape to obtain an optimum pentamaran configuration. Artificial Neural Network (ANN) is adopted to generate a model from the collected data, while the multi-objective optimization is done using Genetic Algorithms (GA). ANN model delivers accurate prediction of resistance with an error of 0.24%. The results show wave resistance and total resistance are reduced by 1.47% and 4.06% for the Froude number greater than 0.4.