Hybrid Genetic Algorithm and Simulated Annealing for Function Optimization
| Main Authors: | Fatyanosa, Tirana Noor, Sihananto, Andreas Nugroho, Alfarisy, Gusti Ahmad Fanshuri, Burhan, M Shochibul, Mahmudy, Wayan Firdaus |
|---|---|
| Format: | Article info application/pdf Journal |
| Bahasa: | eng |
| Terbitan: |
Faculty of Computer Science (FILKOM) Brawijaya University
, 2017
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| Online Access: |
http://jitecs.ub.ac.id/index.php/jitecs/article/view/15 http://jitecs.ub.ac.id/index.php/jitecs/article/view/15/10 |
Daftar Isi:
- 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