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Tirana Noor Fatyanosa
Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering

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Hybrid Genetic Algorithm and Simulated Annealing for Function Optimization Tirana Noor Fatyanosa; Andreas Nugroho Sihananto; Gusti Ahmad Fanshuri Alfarisy; M Shochibul Burhan; Wayan Firdaus Mahmudy
Journal of Information Technology and Computer Science Vol. 1 No. 2: November 2016
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (879.719 KB) | DOI: 10.25126/jitecs.20161215

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
Co-Authors Andreas Nugroho Sihananto Gusti Ahmad Fanshuri Alfarisy M Shochibul Burhan Wayan Firdaus Mahmudy