Solving a Uniform Nonlinear Approximation Problem Using Continuous Genetic Algorithm

2016 ◽  
Vol 48 (6) ◽  
pp. 49-59 ◽  
Author(s):  
Larisa P. Vakal
Keyword(s):  
Genetic Algorithm ◽  
Nonlinear Approximation ◽  
Approximation Problem ◽  
Continuous Genetic Algorithm

Modeling of Electric Springs and Their Multi-Objective Voltage Control Based on Continuous Genetic Algorithm for Unbalanced Distribution Networks

2021 ◽  
Author(s):  
Guillermo Tapia-Tinoco ◽  
David Granados-Lieberman ◽  
Martin Valtierra-Rodriguez ◽  
Juan Gabriel Avina-Cervantes ◽  
Arturo Garcia-Perez
Keyword(s):  
Genetic Algorithm ◽  
Voltage Control ◽  
Distribution Networks ◽  
Multi Objective ◽  
Continuous Genetic Algorithm

scholarly journals Optimal Network Reconfiguration to Reduce Power Loss Using an Initial Searching Point for Continuous Genetic Algorithm

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-21
Author(s):  
Thuan Thanh Nguyen ◽  
Thang Trung Nguyen ◽  
Ngoc Au Nguyen
Keyword(s):  
Genetic Algorithm ◽  
Distribution System ◽  
Power Loss ◽  
Distribution Systems ◽  
Closed Loop ◽  
Control Variable ◽  
Initial Population ◽  
Network Reconfiguration ◽  
Power Loss Reduction ◽  
Continuous Genetic Algorithm

In this paper, an effective method to determine an initial searching point (ISP) of the network reconfiguration (NR) problem for power loss reduction is proposed for improving the efficiency of the continuous genetic algorithm (CGA) to the NR problem. The idea of the method is to close each initial open switch in turn and solve power flow for the distribution system with the presence of a closed loop to choose a switch with the smallest current in the closed loop for opening. If the radial topology constraint of the distribution system is satisfied, the switch opened is considered as a control variable of the ISP. Then, ISP is attached to the initial population of CGA. The calculated results from the different distribution systems show that the proposed CGA using ISP could reach the optimal radial topology with better successful rate and obtained solution quality than the method based on CGA using the initial population generated randomly and the method based on CGA using the initial radial configuration attached to the initial population. As a result, CGA using ISP can be a favorable method for finding a more effective radial topology in operating distribution systems.

scholarly journals Optimization Solution of Troesch’s and Bratu’s Problems of Ordinary Type Using Novel Continuous Genetic Algorithm

2014 ◽  
Vol 2014 ◽  
pp. 1-15 ◽  
Author(s):  
Zaer Abo-Hammour ◽  
Omar Abu Arqub ◽  
Shaher Momani ◽  
Nabil Shawagfeh
Keyword(s):  
Genetic Algorithm ◽  
Parallel Machines ◽  
Optimization Technique ◽  
Difference Quotient ◽  
Physical Problems ◽  
Second Derivatives ◽  
Ordinary Type ◽  
Global Nature ◽  
Application Fields ◽  
Continuous Genetic Algorithm

A new kind of optimization technique, namely, continuous genetic algorithm, is presented in this paper for numerically approximating the solutions of Troesch’s and Bratu’s problems. The underlying idea of the method is to convert the two differential problems into discrete versions by replacing each of the second derivatives by an appropriate difference quotient approximation. The new method has the following characteristics. First, it should not resort to more advanced mathematical tools; that is, the algorithm should be simple to understand and implement and should be thus easily accepted in the mathematical and physical application fields. Second, the algorithm is of global nature in terms of the solutions obtained as well as its ability to solve other mathematical and physical problems. Third, the proposed methodology has an implicit parallel nature which points to its implementation on parallel machines. The algorithm is tested on different versions of Troesch’s and Bratu’s problems. Experimental results show that the proposed algorithm is effective, straightforward, and simple.

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