Hull Form Parameterization Technique with Local and Global Optimization Algorithms
نویسنده
چکیده
The paper is presented on the development of a designer friendly hull form parameterization and its coupling with a local and a global optimization algorithm: the well known Sequential Quadratic Programming (SQP) and the more recent evolutionary Particle Swarm Optimization (PSO). These two algorithms are representative of classes with rather opposite characteristics (derivative–based and derivative–free, respectively) and their relative performances in solving some typical ship design optimization problem will be discussed in the paper. Following a well known naval architect’s design practice, a parametric modification tool is developed for modifying the ship’s geometry. The original geometry can be easily deformed by direct selection of some standard design parameters and useful information about the effect of the changing in the parameters are immediately obtained and visualized. At the same time, design parameters are assumed as design variables in the formulation of the optimization problem. In the examples, both potential flow and RANS solvers have been used. Numerical results for both single and multi-objective problems are presented.
منابع مشابه
The Global Optimization Geometry of Low-Rank Matrix Optimization
In this paper we characterize the optimization geometry of a matrix factorization problem where we aim to find n×r and m×r matrices U and V such that UV T approximates a given matrixX. We show that the objective function of the matrix factorization problem has no spurious local minima and obeys the strict saddle property not only for the exact-parameterization case where rank(X) = r, but also f...
متن کاملA Meta-heuristic Algorithm for Global Numerical Optimization Problems inspired by Vortex in fluid physics
One of the most important issues in engineering is to find the optimal global points of the functions used. It is not easy to find such a point in some functions due to the reasons such as large number of dimensions or inability to derive them from the function. Also in engineering modeling, we do not have the relationships of many functions, but we can input and output them as a black box. The...
متن کاملShip Hull Form Optimization using Artificial Bee Colony Algorithm
In this paper, artificial bee colony (ABC) algorithms are introduced to optimize ship hull forms for reduced drag. Two versions of ABC algorithm are used: one is the basic ABC algorithm, and the other is an improved artificial bee colony (IABC) algorithm. A recently developed fast flow solver based on the Neumann-Michell theory is used to evaluate the drag of the ship in the optimization proces...
متن کاملA Discrete Hybrid Teaching-Learning-Based Optimization algorithm for optimization of space trusses
In this study, to enhance the optimization process, especially in the structural engineering field two well-known algorithms are merged together in order to achieve an improved hybrid algorithm. These two algorithms are Teaching-Learning Based Optimization (TLBO) and Harmony Search (HS) which have been used by most researchers in varied fields of science. The hybridized algorithm is called A Di...
متن کاملMulti-objective Grasshopper Optimization Algorithm based Reconfiguration of Distribution Networks
Network reconfiguration is a nonlinear optimization procedure which calculates a radial structure to optimize the power losses and improve the network reliability index while meeting practical constraints. In this paper, a multi-objective framework is proposed for optimal network reconfiguration with the objective functions of minimization of power losses and improvement of reliability index. T...
متن کامل