Eliciting User Perceptions Using Assessment Tests Based on an Interactive Genetic Algorithm

2013 ◽  
Vol 135 (3) ◽  
Author(s):  
Emilie Poirson ◽  
Jean-François Petiot ◽  
Ludivine Boivin ◽  
David Blumenthal
Keyword(s):  
Genetic Algorithm ◽  
Product Innovation ◽  
Computer Aided Design ◽  
Graphical Interface ◽  
User Perception ◽  
Interactive Genetic Algorithm ◽  
User Perceptions ◽  
Tuning Parameters ◽  
Assessment Tests ◽  
Aided Design

To avoid failures in the marketplace, the control of the risks in product innovation and the reduction of the innovation cycles require fast and valid assessments from customers. An interactive genetic algorithm (IGA) is proposed for eliciting users' perceptions about the shape of a product, in order to stimulate creativity and to identify design trends. Interactive users' assessment tests are conducted on virtual products to capture and analyze users' responses. The IGA is interfaced with Computer Aided Design (CAD) software (CATIA V5) to create sets of parameterized designs in real time, which are presented iteratively by a graphical interface to the users for evaluation. After a description of the IGA, a study on the convergence of the IGA is presented. The convergence varies, according to the tuning parameters of the algorithm and the size of the design problem. An experiment was carried out with a set of 45 users on the application case, a dashboard, put forward by Renault. The implementation of the perceptive tests and the analysis of the results are described using hierarchical ascendant classification (HAC) and multivariate analysis. This paper shows how the results of tests using IGA can be used to elicit user perception and to detect design trends.

scholarly journals Detecting Design Trends Using Perceptive Tests Based on an Interactive Genetic Algorithm

2011 ◽  
Author(s):  
Emilie Poirson ◽  
Jean-Franc¸ois Petiot ◽  
Julien Be´nabe`s ◽  
Ludivine Boivin ◽  
David Blumenthal
Keyword(s):  
Genetic Algorithm ◽  
Real Time ◽  
Design Problem ◽  
Product Innovation ◽  
Graphical Interface ◽  
User Perception ◽  
Interactive Genetic Algorithm ◽  
Tuning Parameters ◽  
Assessment Tests ◽  
The Creation

To avoid flops, the control of the risks in product innovation and the reduction of the innovation cycles require valid and fast customer’s assessments. An Interactive Genetic algorithm is proposed for eliciting user’s perceptions concerning the shape of a product, in order to stimulate creativity and detecting design trends. Interactive users’ assessment tests are conducted on virtual products, for capturing and analyzing users’ responses. The IGA is interfaced with a CAD software (CATIA V5) and allows the creation in real time of a set of parameterized designs, which are presented iteratively by a graphical interface to the user for evaluation. After a description of the IGA, we present a study on the convergence of the IGA, according to the tuning parameters of the algorithm and the size of the design problem. An experiment was carried out with a set of 20 users on a particular product, table glasses. We describe the implementation of the perceptive tests and an analysis of the results. These results show how the IGA can be used to elicit user perception and detecting design trends.

scholarly journals Finocyl Grain Design Using the Genetic Algorithm in Combination with Adaptive Basis Function Construction

2019 ◽  
Vol 2019 ◽  
pp. 1-12
Author(s):  
Saeed Mesgari ◽  
Mehrdad Bazazzadeh ◽  
Alireza Mostofizadeh
Keyword(s):  
Genetic Algorithm ◽  
Level Set Method ◽  
Level Set ◽  
Computer Aided Design ◽  
Optimization Design ◽  
Design Method ◽  
Burning Surface ◽  
Aided Design ◽  
Function Construction

This study deals with the application of optimization in Finocyl grain design with ballistic objective functions using a genetic algorithm. The classical sampling method is used for space filling; a level-set method is used for simulating the evaluation of a burning surface of the propellant grain. An algorithm is developed beside the level-set code that prepares the initial grain configuration using a computer-aided design (CAD) to export generated models to the level-set code. The lumped method is used to perform internal ballistic analysis. A meta-model is used to surrogate the level-set method in an optimization design loop. Finally, a case study is done to verify the proposed algorithm. Observed results show that the grain design method reduced the design time significantly, and this algorithm can be used in designing any grain type.

Optimization of Heave Motions for a Four Column Semi-Submersible Based on Genetic Algorithm

2018 ◽  
Author(s):  
Suji Zhu
Keyword(s):  
Genetic Algorithm ◽  
Global Optimization ◽  
Computer Aided Design ◽  
Transfer Functions ◽  
Parametric Modelling ◽  
Optimal Solutions ◽  
Global Optimization Algorithm ◽  
The Past ◽  
Computer Aided ◽  
Aided Design

Semi-submersible is designed with low heave motions compared with conventional ships by utilizing the cancelation effects between pontoons and columns. During the past years, continuous efforts have been devoted to reducing the heave amplitudes considering utilizing dry-tree system. Different concepts of semi-submersible have been proposed with favorable heave response. Deep draft semi-submersibles have been proved to be efficient in reducing the heave motions, and the damper structures under the pontoon may also reduce the heave responses significantly. Those concepts are beyond the conventional semi-submersible design, which may bring high costs for fabrication and installations. During computer-aided design and analysis, optimization algorithms are used to search for the optimal hull configuration. However, due to the restrictions of computer capacities, the global optimization algorithm, in some cases, have difficulties in finding out the optimal solutions without the aid from engineering experience. In this paper, the geometry of a ring-pontoon four-column semi-submersible is generated by parametric modelling. The heave transfer functions at center of gravity are calculated using WADAM. Genetic algorithm is used to find the most favorable heave responses. In the end, the parameters that influence the heave motions are summarized and discussed.

scholarly journals Possibilities of applying structural optimization in building structures computer-aided design systems

2018 ◽  
Vol 251 ◽  
pp. 03017 ◽  
Author(s):  
Andrey Vasilkin
Keyword(s):  
Genetic Algorithm ◽  
Structural Optimization ◽  
Computer Aided Design ◽  
Optimization Method ◽  
Design System ◽  
Building Structures ◽  
Computational Tool ◽  
Computer Aided ◽  
Design Solutions ◽  
Aided Design

For computer-aided design solutions search, a computational tool, which will substantially facilitate designer’s work, has been developed. Structural optimization method – genetic algorithm method is taken as a basis. To accelerate design solutions synthesis, computer-aided design system in the form of a developed computational tool is used. It automatically synthesizes a significant number of design solutions using formalized conditions of strength facility requirements. Then, user compares the solutions upon performance criterion and selects the best options. The article demonstrates possibility of genetic algorithm application for obtaining design solutions through the example of a structural coating plate. The advantage of this method is obviousness in solutions search, visualization of proposed structures and user’s work with the system in dialog mode.

scholarly journals Generative 3D images in a visual evolutionary computing system

2010 ◽  
Vol 7 (1) ◽  
pp. 111-126 ◽  
Author(s):  
Hong Liu
Keyword(s):  
Genetic Algorithm ◽  
Binary Tree ◽  
Computer Aided Design ◽  
Complex Function ◽  
Computing System ◽  
Design System ◽  
3D Images ◽  
Design Evolution ◽  
Complex Functions ◽  
Aided Design

This paper presents a novel computer-aided design system which uses a computational approach to producing 3D images for stimulating creativity of designers. It introduces the genetic algorithm first. Then a binary tree based genetic algorithm is presented. This approach is illustrated by a 3D image generative example, which uses complex function expressions as chromosomes to form a binary tree, and all genetic operations are performed on the binary tree. Corresponding complex functions are processed by MATLAB software to form 3D images of artistic flowers. This generative design is integrated with a visualization interface, which allows designers to interact and select from instances for design evolution. It shows the system is able to enhance the possibility of discovering various potential design solutions.

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