Non-linear optimization applied to preliminary ship design

2012 ◽  
pp. 93-100
Keyword(s):  
Linear Optimization ◽  
Ship Design ◽  
Preliminary Ship Design ◽  
Non Linear

scholarly journals Comparative Analysis of Linear and Non-Linear Programming Techniques for the Optimization of Ship-Machinery Systems

2019 ◽  
Vol 7 (11) ◽  
pp. 403 ◽  
Author(s):  
Baldasso ◽  
Elg ◽  
Haglind ◽  
Baldi
Keyword(s):  
Linear Optimization ◽  
Ship Design ◽  
Data Availability ◽  
Design Phase ◽  
Operational Profile ◽  
Operational Optimization ◽  
Non Linear ◽  
Programming Techniques ◽  
Machinery System ◽  
Selection Of

The selection of a proper machinery system is one of the primary decisions to be taken during the ship-design phase. Nonetheless, this selection is made challenging by the presence of a variety of alternatives, and by the limited data availability at the early stages of the design phase. An optimization framework is presented in this paper, supporting decision making at the earliest stages of the ship-design process. The framework is suitable to perform the screening and the selection of optimal machinery configurations for a predefined ship operational profile, and it includes both linear and non-linear optimization routines. The results of the linear and the non-linear approaches are compared, and indications on what conditions are the most suitable for the application of one or the other approach are provided. Both approaches are tested for two case studies, a bulk carrier and a small cruise ship. The results indicate that both optimization approaches lead to the same layout of the machinery system, but to slightly different unit scheduling. This suggests that the use of the linear approach is suitable for design purposes, but less appropriate for operational optimization. In addition, the findings of the work suggest that the trade-off between fuel consumption and volume of the engines should be considered when selecting the machinery system for a ship.

Computer Representation of Numerical Expertise for Preliminary Ship Design

1989 ◽  
Vol 26 (04) ◽  
pp. 289-302
Author(s):  
A. H. B. Duffy ◽  
K. J. MacCallum
Keyword(s):  
Experimental System ◽  
Ship Design ◽  
Design Model ◽  
Design System ◽  
Early Stages ◽  
Worked Example ◽  
Preliminary Ship Design ◽  
Numerical Design ◽  
Computer Representation ◽  
Computer Based

In the early stages of ship design a considerable amount of experience and knowledge is used to build and evaluate empirical models with known design relationships. However, computer-based systems which aim to assist this stage have tended to concentrate on the analytical aspects of the process and have not been successful in integrating with this expertise and benefitting from it. This paper presents some of the results of a program of research into methods and representing knowledge of empirical numerical relationships used in these early stages of the design process. The work is based on an experimental system, DESIGNER, described in earlier papers. The DESIGNER system is used to carry out a series of evaluations of design sessions, using a warship design model. By examining the progress toward a set of design goals and the classes of interactions used, an improved understanding of the requirements of an interactive numerical design system is developed. As a consequence, methods have been developed to handle approximate values and relationships, to include design margins, and to represent explicitly in the system the definition and use of goals, or design requirements. Using a design model representing a bulk carrier, the paper then presents a worked example to illustrate the use of the new numerical knowledge techniques. It is concluded that the techniques could make a useful contribution to any interactive numerical design system which aims to provide improved use of expertise.

scholarly journals Design of a New Synthetic Acceptance Sampling Plan

Symmetry ◽  
2018 ◽  
Vol 10 (11) ◽  
pp. 653 ◽  
Author(s):  
Saeed Dobbah ◽  
Muhammad Aslam ◽  
Khushnoor Khan
Keyword(s):  
Standard Deviation ◽  
Normal Distribution ◽  
Operating Characteristic ◽  
Linear Optimization ◽  
Sampling Plan ◽  
Quality Characteristic ◽  
Acceptance Sampling ◽  
Acceptance Sampling Plan ◽  
Non Linear

In this paper, we propose a new synthetic sampling plan assuming that the quality characteristic follows the normal distribution with known and unknown standard deviation. The proposed plan is given and the operating characteristic (OC) function is derived to measure the performance of the proposed sampling plan for some fixed parameters. The parameters of the proposed sampling plan are determined using non-linear optimization solution. A real example is added to explain the use of the proposed plan by industry.

scholarly journals Hybrid Genetic Algorithm and Simulated Annealing for Function Optimization

2017 ◽  
Vol 1 (2) ◽  
pp. 82 ◽  
Author(s):  
Tirana Noor Fatyanosa ◽  
Andreas Nugroho Sihananto ◽  
Gusti Ahmad Fanshuri Alfarisy ◽  
M Shochibul Burhan ◽  
Wayan Firdaus Mahmudy
Keyword(s):  
Genetic Algorithm ◽  
Simulated Annealing ◽  
Optimization Problems ◽  
Linear Optimization ◽  
Hybrid Genetic Algorithm ◽  
Optimal Solution ◽  
Function Optimization ◽  
Non Linear ◽  
Speed Up ◽  
Linear Problems

The optimization problems on real-world usually have non-linear characteristics. Solving non-linear problems is time-consuming, thus heuristic approaches usually are being used to speed up the solution’s searching. Among of the heuristic-based algorithms, Genetic Algorithm (GA) and Simulated Annealing (SA) are two among most popular. The GA is powerful to get a nearly optimal solution on the broad searching area while SA is useful to looking for a solution in the narrow searching area. This study is comparing performance between GA, SA, and three types of Hybrid GA-SA to solve some non-linear optimization cases. The study shows that Hybrid GA-SA can enhance GA and SA to provide a better result

Sign in / Sign up

Export Citation Format

Share Document