A study of genetic algorithm approaches to global geometry optimization of aromatic hydrocarbon microclusters

1998 ◽  
Vol 108 (5) ◽  
pp. 2208-2218 ◽  
Author(s):  
Ronald P. White ◽  
J. A. Niesse ◽  
Howard R. Mayne
Keyword(s):  
Genetic Algorithm ◽  
Aromatic Hydrocarbon ◽  
Geometry Optimization ◽  
Global Geometry

Global geometry optimization of (Ar)n and B(Ar)n clusters using a modified genetic algorithm

1996 ◽  
Vol 104 (7) ◽  
pp. 2684-2691 ◽  
Author(s):  
Susan K. Gregurick ◽  
Millard H. Alexander ◽  
Bernd Hartke
Keyword(s):  
Genetic Algorithm ◽  
Geometry Optimization ◽  
Global Geometry ◽  
Modified Genetic Algorithm

scholarly journals Global geometry optimization of water clusters (H2O)n≤14)using a single-parent genetic algorithm

2007 ◽  
Vol 56 (5) ◽  
pp. 2553
Author(s):  
Zhang Su_Ling ◽  
Chen Hong_Shan ◽  
Song Yan ◽  
Yin Yue_Hong
Keyword(s):  
Genetic Algorithm ◽  
Water Clusters ◽  
Geometry Optimization ◽  
Single Parent ◽  
Global Geometry

scholarly journals DNA-stabilized Ag–Au bimetallic clusters: the effects of alloying and embedding on optical properties

2016 ◽  
Vol 18 (32) ◽  
pp. 22311-22322 ◽  
Author(s):  
Dennis Palagin ◽  
Jonathan P. K. Doye
Keyword(s):  
Optical Properties ◽  
Density Functional ◽  
Geometry Optimization ◽  
Structural Evolution ◽  
Density Functional Theory Calculations ◽  
Time Dependent ◽  
Bimetallic Clusters ◽  
Functional Theory ◽  
Global Geometry ◽  
Dependent Density

Global geometry optimization and time-dependent density functional theory calculations have been used to study the structural evolution and optical properties of AgnAun (n = 2–6) nanoalloys both as individual clusters and as clusters stabilized with the fragments of DNA of different size.

scholarly journals Comparison of Genetic Algorithm and Harmony Search Method for 2D Geometry Optimization.

2018 ◽  
Vol 159 ◽  
pp. 01009 ◽  
Author(s):  
Mohammad Ghozi ◽  
Anik Budiati
Keyword(s):  
Genetic Algorithm ◽  
Harmony Search ◽  
Geometry Optimization ◽  
Steel Structure ◽  
Search Method ◽  
Geometric Optimization ◽  
Computational Time ◽  
Time Required ◽  
Average Computational Time ◽  
Better Than

There are many applications of Genetic Algorithm (GA) and Harmony Search (HS) Method for solving problems in civil engineering design. The question is, still, which method is better for geometry optimization of a steel structure. The purpose of this paper is to compare GA and HS performance for geometric optimization of a steel structure. This problem is solved by optimizing a steel structure using GA and HS and then comparing the structure’s weight as well as the time required for the calculation. In this study, GA produced a structural weight of 2308.00 kg to 2387.00 kg and HS scored 2193.12 kg to 2239.48 kg. The average computational time required by GA is 607 seconds and HS needed 278 seconds. It concludes that HS is faster and better than GA for geometry optimization of a steel structure.

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