Test Vector Reordering by using Hybrid Genetic Algorithm-Simulated Annealing for Lower Switching Activity

2018 ◽  
Author(s):  
Karri Vivek Reddy ◽  
Malapati Venkata Bharath ◽  
Ashok Kumar Suhag ◽  
Mohit Sinha
Keyword(s):  
Genetic Algorithm ◽  
Simulated Annealing ◽  
Hybrid Genetic Algorithm ◽  
Test Vector ◽  
Switching Activity

scholarly journals Hybrid Genetic Algorithm and Simulated Annealing for Function Optimization

2017 ◽  
Vol 1 (2) ◽  
pp. 82 ◽  
Author(s):  
Tirana Noor Fatyanosa ◽  
Andreas Nugroho Sihananto ◽  
Gusti Ahmad Fanshuri Alfarisy ◽  
M Shochibul Burhan ◽  
Wayan Firdaus Mahmudy
Keyword(s):  
Genetic Algorithm ◽  
Simulated Annealing ◽  
Optimization Problems ◽  
Linear Optimization ◽  
Hybrid Genetic Algorithm ◽  
Optimal Solution ◽  
Function Optimization ◽  
Non Linear ◽  
Speed Up ◽  
Linear Problems

The optimization problems on real-world usually have non-linear characteristics. Solving non-linear problems is time-consuming, thus heuristic approaches usually are being used to speed up the solution’s searching. Among of the heuristic-based algorithms, Genetic Algorithm (GA) and Simulated Annealing (SA) are two among most popular. The GA is powerful to get a nearly optimal solution on the broad searching area while SA is useful to looking for a solution in the narrow searching area. This study is comparing performance between GA, SA, and three types of Hybrid GA-SA to solve some non-linear optimization cases. The study shows that Hybrid GA-SA can enhance GA and SA to provide a better result

Engineering-Oriented Hybrid Genetic Algorithm for Frequency Assignment Problem

2010 ◽  
Vol 40-41 ◽  
pp. 410-418
Author(s):  
Ting Ting Zhou ◽  
Ying Zheng ◽  
Ming Chen
Keyword(s):  
Genetic Algorithm ◽  
Particle Swarm Optimization ◽  
Simulated Annealing ◽  
Assignment Problem ◽  
Hybrid Genetic Algorithm ◽  
Mobile Telephone ◽  
Frequency Assignment ◽  
Real Word ◽  
Frequency Assignment Problem ◽  
Swarm Optimization

Since the usable range of the frequency spectrum is limited, the frequency assignment problem (FAP) is important in mobile telephone communication. In this paper, according to the characteristics of engineering- oriented FAP, an engineering-oriented hybrid genetic algorithm (EHGA) based on traditional genetic algorithm (TGA) is proposed, combined with particle swarm optimization (PSO) and simulated annealing (SA). The results obtained by the simulation to a real-word FAP case in GSM show that the algorithm we proposed is a better approach to solve the engineering-oriented FAP.

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