A Genetic Algorithm Optimization Method for Mapping Non-Conducting Atrial Regions: A Theoretical Feasibility Study

2015 ◽  
Vol 7 (1) ◽  
pp. 87-101 ◽  
Author(s):  
Shai Shiff ◽  
Moshe Swissa ◽  
Sharon Zlochiver
Keyword(s):  
Genetic Algorithm ◽  
Feasibility Study ◽  
Optimization Method ◽  
Algorithm Optimization ◽  
Genetic Algorithm Optimization

scholarly journals Robust Hybrid Optimization Method to Reduce Investment Portfolio Risk using Fusion of Modern Portfolio Theory and Genetic Algorithm

2019 ◽  
Vol 8 (6S3) ◽  
pp. 136-148
Keyword(s):  
Genetic Algorithm ◽  
Optimization Method ◽  
Portfolio Theory ◽  
Hybrid Optimization ◽  
Investment Risk ◽  
Portfolio Risk ◽  
Algorithm Optimization ◽  
Investment Portfolio ◽  
Genetic Algorithm Optimization ◽  
Modern Portfolio Theory

Main objective of this study is to develop hybrid optimization method for reducing investment portfolio risk. The methods selected in this study are the combination of Modern Portfolio Theory (MPT) and genetic algorithm optimization approach. Three stocks from Malaysian Stock Exchange are selected in developing the investment portfolio namely Malayan Banking Berhad, Hap Seng Consolidated Berhad and Top Glove Corporation Berhad. Result indicates the modern portfolio theory can give optimal portfolio weightage with maximum return for tolerate level of investment risk. In addition, genetic algorithm enhanced the optimal searching method to find global minimum of investment risk. Result shows the minimum portfolio risk in objective function is 2.122118 with implementation genetic algorithm optimization. The optimal combination of portfolio investment is 32.24 % in asset A (Malayan Banking Berhad), 52.37 % in asset B (Hap Seng Consolidated Berhad), and 15.30 % in asset C (Top Gove Corporation Berhad). The important of this study is it will assist investor in making better decision to optimize their return for given level of investment risk. Furthermore, this hybrid method provides a better accuracy of prediction for return of investment and portfolio risk.

GA-CDFM Based Hybrid Optimization Method for Steelmaking Scheduling and Caster Operation

2012 ◽  
Vol 424-425 ◽  
pp. 994-998 ◽  
Author(s):  
Xiao Chuan Luo ◽  
Chong Zheng Na
Keyword(s):  
Genetic Algorithm ◽  
Integer Programming ◽  
Mixed Integer Programming ◽  
Programming Model ◽  
Optimization Method ◽  
Optimal Performance ◽  
Hybrid Optimization ◽  
Mixed Integer ◽  
Algorithm Optimization ◽  
Genetic Algorithm Optimization

In steelmaking plant, the process times of machines change frequently and randomly for the reason of metallurgical principle. When those change happen, the plant scheduling and caster operation must respond to keep the optimal performance profile of plant. Therefore, the integration of plant scheduling and caster operation is a crucial task. This paper presents a mixed-integer programming model and a hybrid optimized algorithm for caster operation and plant scheduling, which combine the genetic algorithm optimization and CDFM process status verification. Data experiments illustrate the efficiency of our model and algorithm.

Genetic Algorithm Optimization of a Double Four-Bar Manipulator

2013 ◽  
Vol 834-836 ◽  
pp. 1323-1326
Author(s):  
Qi Jing Tang ◽  
Tie Shi Zhao
Keyword(s):  
Genetic Algorithm ◽  
Mathematical Model ◽  
Structural Strength ◽  
Optimization Method ◽  
Installation Space ◽  
Algorithm Optimization ◽  
Genetic Algorithm Optimization ◽  
Transmission Angle ◽  
The Mathematical Model

In order to optimize the dimension of a manipulator, the optimization requirements are analyzed. Then the mathematical model and optimization objectives are established. Next, the lengths of the manipulator are optimized by Matlab genetic algorithm optimization toolbox. The structural strength and bearing installation space are considered at the same time. The trajectory and transmission angle are compared. Finally, the lengths which meet the use requirements are obtained. This optimization method provides a reference for similar mechanism.

scholarly journals Optimization of Watt's Six-Bar Linkage to Generate Straight and Parallel Leg Motion

10.5772/50917 ◽  
2012 ◽  
Vol 9 (1) ◽  
pp. 22 ◽  
Author(s):  
Hamid Mehdigholi ◽  
Saeed Akbarnejad
Keyword(s):  
Genetic Algorithm ◽  
Contact Area ◽  
Optimization Method ◽  
Contact Period ◽  
Algorithm Optimization ◽  
Genetic Algorithm Optimization ◽  
Parallel Motion ◽  
Leg Motion ◽  
Four Bar Linkage ◽  
Curve Equation

This paper considers optimal synthesis of a special type of four-bar linkages. Combination of this optimal four-bar linkage with on of it's cognates and elimination of two redundant cognates will result in a Watt's six-bar mechanism, which generates straight and parallel motion. This mechanism can be utilized for legged machines. The advantage of this mechanism is that the leg remains straight during it's contact period and because of it's parallel motion, the legs can be as wide as desired to increase contact area and decrease the number of legs required to keep body's stability statically and dynamically. “Genetic algorithm” optimization method is used to find optimal lengths. It is especially useful for problems like the coupler curve equation which are completely nonlinear or extremely difficult to solve.

DETERMINATION OF THE STACKING VELOCITY FIELD VIA OPTIMIZATION METHODS

2016 ◽  
Vol 33 (3) ◽  
Author(s):  
Danian Steinkirch de Oliveira ◽  
Milton José Porsani ◽  
Paulo Eduardo Miranda Cunha
Keyword(s):  
Genetic Algorithm ◽  
Velocity Field ◽  
A Priori ◽  
Optimization Methods ◽  
Optimization Method ◽  
A Priori Information ◽  
Algorithm Optimization ◽  
Genetic Algorithm Optimization ◽  
Priori Information

ABSTRACT. We developed a strategy for automatic Semblance panels pick, that uses Genetic Algorithm optimization method. In conjunction with restrictions and penalties set from a priori information... RESUMO. Foi desenvolvida uma estratégia de pick automático dos painéis de Semblance , que usa método de otimização Algorítmo Genético. Em conjunto com restrições...

scholarly journals Boolean regulatory network reconstruction using literature based knowledge with a genetic algorithm optimization method

2016 ◽  
Vol 17 (1) ◽  
Author(s):  
Julien Dorier ◽  
Isaac Crespo ◽  
Anne Niknejad ◽  
Robin Liechti ◽  
Martin Ebeling ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Regulatory Network ◽  
Optimization Method ◽  
Network Reconstruction ◽  
Algorithm Optimization ◽  
Genetic Algorithm Optimization
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