Hybrid Genetic Algorithm and Simulated Annealing for Function Optimization
Abstract: 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
Author: Tirana Noor Fatyanosa,
Andreas Nugroho Sihananto, Gusti Ahmad Fanshuri Alfarisy, M Shochibul Burhan,
Wayan Firdaus Mahmudy
Journal Code: jptinformatikagg160012
