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Automatic Differentiation Based for Particle Swarm Optimization Steepest Descent Direction

Thobirin, Aris and Tri Riyadi Yanto, Iwan (2018) Automatic Differentiation Based for Particle Swarm Optimization Steepest Descent Direction. [Artikel Dosen]

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Abstract

Particle swam optimization (PSO) is one of the most effective optimization methods to find the global optimum point. In other hand, the descent direction (DD) is the gradient based method that has the local search capability. The combination of both methods is promising and interesting to get the method with effective global search capability and efficient local search capability. However, In many application, it is difficult or impossible to obtain the gradient exactly of an objective function. In this paper, we propose Automatic differentiation (AD) based for PSODD. We compare our methods on benchmark function. The results shown that the combination methods give us a powerful tool to find the solution.

Item Type: Artikel Dosen
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisi / Prodi: Faculty of Mathematics and Natural Sciences (Fakultas Matematika dan Ilmu Pengetahuan Alam) > S1-Information System (S1-Sistem Informasi)
Depositing User: Iwan Tri Riyadi Yanto
Date Deposited: 06 Nov 2018 06:59
Last Modified: 06 Nov 2018 06:59
URI: http://eprints.uad.ac.id/id/eprint/11644

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