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      Implementasi Algoritma PSO Ring Topology dan Neighborhood PSO untuk Koordinasi Kilobot dalam Masalah Pencarian Target

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      Date
      2025
      Author
      Murtadho, Ahmad Tedy
      Hardhienata, Medria Kusuma Dewi
      Priandana, Karlisa
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      Abstract
      Pencarian target merupakan salah satu permasalahan di dunia nyata yang sering muncul dalam sistem multi-robot. Penelitian ini mengimplementasikan algoritma PSO ring topology untuk pencarian target dengan menggunakan kilobot dalam lingkungan simulasi. Namun, kilobot memiliki keterbatasan jarak komunikasi sehingga perlu dipertimbangkan penggunaan algoritma dengan topologi komunikasi yang memungkinkan pengiriman data dengan keterbatasan jarak. Untuk mengatasi masalah tersebut, algoritma Neighborhood PSO diterapkan dan diuji dengan memvariasikan jumlah agen untuk menganalisis pengaruh jumlah agen terhadap kinerja algoritma. Hasil pengujian menunjukkan bahwa algoritma PSO ring topology memiliki kinerja yang lebih baik dalam hal persentase agen yang berhasil teralokasi pada target, persentase agen yang berhasil terkoneksi dan kecepatan konvergensi dibandingkan dengan algoritma NPSO. Di lain sisi, Algoritma NPSO menunjukkan peningkatan kinerja seiring bertambahnya jumlah agen yang digunakan.
       
      Target search is a common real-world problem frequently encountered in multi-robot systems. This study initially implemented the ring topology PSO (Particle Swarm Optimization) algorithm for target search using Kilobot in a simulated environment. However, Kilobot has communication range limitations, making the ring topology PSO algorithm impractical for real-world applications. To address this issue, the NPSO (Neighborhood Particle Swarm Optimization) algorithm was applied and tested by varying the number of agents to analyze the effect of agent numbers on algorithm performance. The research results showed that the ring topology PSO algorithm performed better in terms of the percentage of agents successfully allocated to the target and convergence speed compared to the NPSO algorithm. On the other hand, the NPSO algorithm demonstrated performance improvements as the number of agents increased and dynamic inertia weights were applied. Thus, this study concludes that NPSO is a more suitable algorithm for enhancing multi-robot system performance in target search scenarios, considering communication constraints.
       
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      http://repository.ipb.ac.id/handle/123456789/165032
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      • UT - Computer Science [92]

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      Copyright © 2020 Library of IPB University
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      Indonesia DSpace Group 
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