Discrete Optimization of Ship Structures with Genetic Algorithms

Abstract

A discrete optimization method using genetic algorithms is developed for the optimization of ship structures. In this method, the constrained minimization problem is first transformed into an unconstrained one by a penalty term depending on the degree of constraint violation. Since the search procedure of the genetic algorithm is done based on the evaluation of fitness function, the unconstrained minimization problem is further converted into a maximization of the fitness function. The discrete design variables are coded into a binary string of finite length. The search procedure from generation to generation is carried out by a simple genetic algorithm with the genetic operators of reproduction, crossover and mutation. A cargo ship with large hatch opening is taken as the numerical example for the illustration purpose. The influences of penalty coefficient, population size, crossover probability and mutation probability on the optimum design are investigated. The comparison between the genetic algorithm and the multiplier method is also made. It demonstrates that the present method can handle the optimization of ship structures with discrete design variables well.