Application of a Genetic Algorithm to Concept Variant Selection

2006 ◽  
Author(s):  
Ryan S. Hutcheson ◽  
Robert L. Jordan ◽  
Robert B. Stone ◽  
Janis P. Terpenny ◽  
Xiaomeng Chang
Keyword(s):  
Genetic Algorithm ◽  
Product Development ◽  
Solution Space ◽  
Variant Selection ◽  
Functional Modeling ◽  
Detailed Design ◽  
Modeling Techniques ◽  
Break Even Point ◽  
Future Work ◽  
Selection Of

This paper outlines a framework for applying a genetic algorithm to the selection of component variants between the conceptual and detailed design stages of product development. A genetic algorithm (GA) is defined for the problem and an example is presented that demonstrates its application and usefulness. Functional modeling techniques are used to formulate the design problem and generate the chromosomes that are evaluated with the algorithm. In the presented example, suitable GA parameters and the break-even point where the GA surpassed an enumerated search of the same solution space were found. Recommend uses of the GA along with limitations of the method and future work are presented as well.

Comparative study of genetic algorithm and simulated annealing for optimal tolerance design formulated with discrete and continuous variables

2005 ◽  
Vol 219 (10) ◽  
pp. 735-758 ◽  
Author(s):  
P K Sing ◽  
S C Jain ◽  
P K Jain
Keyword(s):  
Genetic Algorithm ◽  
Simulated Annealing ◽  
Design Problem ◽  
Optimal Solution ◽  
Solution Space ◽  
Optimization Techniques ◽  
Manufacturing Processes ◽  
Tolerance Design ◽  
Solution Algorithms ◽  
Selection Of

Optimal tolerance design has been the focus of extensive research for a few decades. This has resulted in several formulations and solution algorithms for systematic tolerance design considering various aspects. Availability of different alternative manufacturing processes or machines for realization of a dimension is frequently encountered. In such cases optimal tolerance design must also consider optimal selection of a set of manufacturing processes or machines as appropriate. Such a non-linear multivariate optimal tolerance design problem results in a combinatorial and multi-modal solution space. Optimal solution of this advanced tolerance design problem is difficult using traditional optimization techniques. The problem formulation becomes more complex with simultaneous selection of design and manufacturing tolerances. The focus of the current research is on the optimal solution of this advanced and complex tolerance design problem. Genetic algorithm and simulated annealing as non-traditional global optimization techniques have been used to obtain the solution. Application of the solution techniques has been demonstrated with the help of appropriate examples. Comparison of the results establishes that the genetic algorithm is the superior of the two approaches.

Feature selection of the armature winding broken coils in synchronous motor using genetic algorithm and mahalanobis distance

2012 ◽  
Vol 57 (3) ◽  
pp. 829-835 ◽  
Author(s):  
Z. Głowacz ◽  
J. Kozik
Keyword(s):  
Genetic Algorithm ◽  
Feature Selection ◽  
Mahalanobis Distance ◽  
Distance Measure ◽  
Synchronous Motor ◽  
Medical Diagnostics ◽  
Motor Current ◽  
Feature Spaces ◽  
Multidimensional Feature Spaces ◽  
Selection Of

The paper describes a procedure for automatic selection of symptoms accompanying the break in the synchronous motor armature winding coils. This procedure, called the feature selection, leads to choosing from a full set of features describing the problem, such a subset that would allow the best distinguishing between healthy and damaged states. As the features the spectra components amplitudes of the motor current signals were used. The full spectra of current signals are considered as the multidimensional feature spaces and their subspaces are tested. Particular subspaces are chosen with the aid of genetic algorithm and their goodness is tested using Mahalanobis distance measure. The algorithm searches for such a subspaces for which this distance is the greatest. The algorithm is very efficient and, as it was confirmed by research, leads to good results. The proposed technique is successfully applied in many other fields of science and technology, including medical diagnostics.

scholarly journals Regulating the Regulators: Mechanisms of Substrate Selection of the O-GlcNAc Cycling Enzymes OGT and OGA

Glycobiology ◽  
2021 ◽  
Author(s):  
Hannah M Stephen ◽  
Trevor M Adams ◽  
Lance Wells
Keyword(s):  
Nutrient Sensing ◽  
Substrate Selection ◽  
Disease States ◽  
Dynamic Modification ◽  
Selection For ◽  
Outstanding Question ◽  
Glcnac Transferase ◽  
Future Work ◽  
Partner Proteins ◽  
Selection Of

Abstract Thousands of nuclear and cytosolic proteins are modified with a single β-N-acetylglucosamine on serine and threonine residues in mammals, a modification termed O-GlcNAc. This modification is essential for normal development and plays important roles in virtually all intracellular processes. Additionally, O-GlcNAc is involved in many disease states, including cancer, diabetes, and X-linked intellectual disability. Given the myriad of functions of the O-GlcNAc modification, it is therefore somewhat surprising that O-GlcNAc cycling is mediated by only two enzymes: the O-GlcNAc transferase (OGT), which adds O-GlcNAc, and the O-GlcNAcase (OGA), which removes it. A significant outstanding question in the O-GlcNAc field is how do only two enzymes mediate such an abundant and dynamic modification. In this review, we explore the current understanding of mechanisms for substrate selection for the O-GlcNAc cycling enzymes. These mechanisms include direct substrate interaction with specific domains of OGT or OGA, selection of interactors via partner proteins, posttranslational modification of OGT or OGA, nutrient sensing, and localization alteration. Altogether, current research paints a picture of an exquisitely regulated and complex system by which OGT and OGA select substrates. We also make recommendations for future work, toward the goal of identifying interaction mechanisms for specific substrates that may be able to be exploited for various research and medical treatment goals.

scholarly journals A Qualitative Study of COVID-19 Distress in University Students

2021 ◽  
pp. 216769682110251
Author(s):  
Samantha G. Farris ◽  
Mindy M. Kibbey ◽  
Erick J. Fedorenko ◽  
Angelo M. DiBello
Keyword(s):  
University Students ◽  
Undergraduate Students ◽  
Mental Health Problems ◽  
Financial Strain ◽  
Public Response ◽  
Viral Spread ◽  
Future Work ◽  
The Impact ◽  
Viral Outbreak ◽  
Selection Of

The psychological effect of the pandemic and measures taken in response to control viral spread are not yet well understood in university students; in-depth qualitative analysis can provide nuanced information about the young adult distress experience. Undergraduate students ( N = 624) in an early US outbreak “hotspot” completed an online narrative writing about the impact and distress experienced due to the COVID-19 pandemic. Data were collected April-May 2020. A random selection of 50 cases were sampled for thematic analysis. Nine themes were identified: viral outbreak distress, fear of virus contraction/transmission, proximity to virus, dissatisfaction with public response, physical distancing distress, social distancing distress, academic and school-related distress, disruptive changes in health behavior and routines, financial strain and unemployment, worsening of pre-existing mental health problems, and social referencing that minimizes distress. Future work is needed to understand the persistence of the distress, in addition to developing methods for assessment, monitoring, and mitigation of the distress.

scholarly journals Strain Accommodations among Twin Variants in Ti and Mg

Crystals ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 453
Author(s):  
Ping Zhou ◽  
Guo-Zhen Zhu
Keyword(s):  
Mechanical Property ◽  
Great Influence ◽  
Local Strain ◽  
Deformation Texture ◽  
Variant Selection ◽  
Slip Systems ◽  
Twinning Shear ◽  
Active Variant ◽  
Shed Light ◽  
Selection Of

The selection of twin variants has a great influence on deformation texture and mechanical property in hcp metals where slip systems are limited and twinning types are abundant during deformation. Local strain accommodations among twin variants are considered to shed light on variant selection rules in Ti and Mg alloys. Five kinds of strain accommodations are discussed in terms of different regions that are affected by the twinning shear of primary twin. These regions contain (I) the whole sample, (II) neighboring grain, (III) adjacent primary twin in neighboring grain, (IV) adjoining primary twin within the same parent grain, and (V) multi-generation of twinning inside the primary twin. For a potentially active variant, its operation needs not only relatively higher resolved shear stress but also easily accommodated strain by immediate vicinity. Many of the non-Schmid behaviors could be elucidated by local strain accommodations that variants with relatively higher SFs hard to be accommodated are absent, while those with relatively lower SFs but could be easily accommodated are present.

scholarly journals Selection of Scholarship Recipient by Implementing Genetic Algorithm and Fuzzy Logic

2021 ◽  
Vol 1933 (1) ◽  
pp. 012069
Author(s):  
Yohanssen Pratama ◽  
Monalisa Pasaribu ◽  
Joni Nababan ◽  
Dayani Sihombing ◽  
Dicky Gultom
Keyword(s):  
Genetic Algorithm ◽  
Fuzzy Logic ◽  
Selection Of

Selection of Input Variables for the Prediction of Wind Speed in Wind Farms Based on Genetic Algorithm

2011 ◽  
Vol 35 (6) ◽  
pp. 649-660 ◽  
Author(s):  
R. A. Gupta ◽  
Rajesh Kumar ◽  
Ajay Kumar Bansal
Keyword(s):  
Genetic Algorithm ◽  
Wind Speed ◽  
Wind Farms ◽  
Input Variables ◽  
Selection Of

Strain compatibility effect on the variant selection of connected twins in magnesium

2015 ◽  
Vol 76 ◽  
pp. 71-76 ◽  
Author(s):  
Changfa Guo ◽  
Renlong Xin ◽  
Jianbin Xu ◽  
Bo Song ◽  
Qing Liu
Keyword(s):  
Compatibility Effect ◽  
Variant Selection ◽  
Strain Compatibility ◽  
Selection Of

Optimum Selection of Hydraulic Devices for Water Hammer Control in the Pipeline Systems Using Genetic Algorithm

2003 ◽  
Author(s):  
Bong Seong Jung ◽  
Bryan W. Karney
Keyword(s):  
Genetic Algorithm ◽  
Steady State ◽  
Optimization Problems ◽  
System Optimization ◽  
Water Hammer ◽  
Pipeline System ◽  
Optimal Size ◽  
Protection Strategy ◽  
Hydraulic Devices ◽  
Selection Of

Genetic algorithms have been used to solve many water distribution system optimization problems, but have generally been limited to steady state or quasi-steady state optimization. However, transient events within pipe system are inevitable and the effect of water hammer should not be overlooked. The purpose of this paper is to optimize the selection, sizing and placement of hydraulic devices in a pipeline system considering its transient response. A global optimal solution using genetic algorithm suggests optimal size, location and number of hydraulic devices to cope with water hammer. This study shows that the integration of a genetic algorithm code with a transient simulator can improve both the design and the response of a pipe network. This study also shows that the selection of optimum protection strategy is an integrated problem, involving consideration of loading condition, device and system characteristics, and protection strategy. Simpler transient control systems are often found to outperform more complex ones.

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