MODIFIED PARTICLE SWARM OPTIMIZATION WITH CHAOS-BASED PARTICLE INITIALIZATION AND LOGARITHMIC DECREASING INERTIA WEIGHT
Penulis/Author
MURINTO (1); Prof. Drs. Agus Harjoko, M.Sc., Ph.D. (2); Prof. Dra. Sri Hartati, M.Sc., Ph.D. (3); Prof. Drs. Projo Danoedoro, M.Sc., Ph.D. (4)
Tanggal/Date
2021
Kata Kunci/Keyword
Abstrak/Abstract
The global optimization problem can be solved using one of the algorithms, namely Particle swarm optimization (PSO). The PSO algorithm is a population optimization based on swarm intelligence, which has been widely studied and is widely applied to various problems. However, PSO is often trapped in local optimal and premature convergence on complex multimodal function problems. To solve this problem, a variant of particle swarm optimization involves the chaos maps mechanism strategy and the inertia weight of standard particle swarm optimization. Chaos map is used to produce uniform particle distribution to improve the quality of the initial position of the particles. While the inertia weight used here is logarithmic decreasing inertia weight (LogDIW) to help the algorithm get out of the local optimal and make the particles continue to search in other areas of the solution space. Extensive experiments on six well-known benchmark functions with different dimensions show that the proposed PSO is superior or very competitive to several other PSO variants in dealing with complex multimodal problems.
Rumpun Ilmu
Ilmu Komputer
Bahasa Asli/Original Language
English
Level
Internasional
Status
Dokumen Karya
No
Judul
Tipe Dokumen
Aksi
1
home-icicel.pdf
[PAK] Halaman Cover
2
Editorial board - ICIC-EL.pdf
[PAK] Halaman Editorial
3
turnitin-MODIFIED PSO.pdf
[PAK] Cek Similarity
4
ICIC-EL-16-02 Modified PSO - lengkap-PAK-low.pdf
[PAK] Full Dokumen
5
murinto_lulus1.pdf
Dokumen Pendukung Karya Ilmiah (Hibah, Publikasi, Penelitian, Pengabdian)
6
murinto_lulus2.pdf
Dokumen Pendukung Karya Ilmiah (Hibah, Publikasi, Penelitian, Pengabdian)
