Multi-Criteria Weights on Ad Hoc Networks Using Particle Swarm Optimization for Optimal Path Pairs

Gunantara, Nyoman; Sudiarta, Pande Ketut; Antara, I Nyoman Gde

doi:10.15866/iree.v13i1.14082

Cited by 6 publications

(6 citation statements)

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“…e combination of path pairs that can occur can be in the form of a pair of path consisting of 1 hop with 2 hops, 2 hops with 2 hops, 2 hops with 3 hops, 3 hops with 3 hops, or others. In this research, the maximum number of hops considered for a path is limited to 3. e combination of the path pairs that occur for the 3 hops with 3 hops is [12]. Selection of nodes in an ad hoc network to form a path can be done based on the criteria used.…”

Section: Ad Hoc Network and Scalarizationmentioning

confidence: 99%

“…In this study, various multicriteria, namely, SNR, load variance, and power consumption, are used. Mathematical equations, path pairs, and optimal path pairs of each criterion used have been determined [12].…”

Section: Ad Hoc Network and Scalarizationmentioning

confidence: 99%

“…e comparison between GA and PSO methods is done to find out the feature and the effectiveness in the simulation. It is also used to choose path pair in an ad hoc network with multiple criteria with rank sum weights [12].…”

Section: Introductionmentioning

confidence: 99%

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The Characteristics of Metaheuristic Method in Selection of Path Pairs on Multicriteria Ad Hoc Networks

Gunantara

Putra

2019

Journal of Computer Networks and Communications

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This research analyzes the metaheuristic methods, that is, ant colony optimization (ACO), genetic algorithm (GA), and particle swarm optimization (PSO), in the selection of path pairs on multicriteria ad hoc network. Multicriteria used are signal-to-noise ratio (SNR), load variance, and power consumption. Analysis of the simulation result is done as follows: first, in terms of computing time, the ACO method takes the most time compared with GA and PSO methods. Second, in terms of multicriteria performance, i.e., the performance of SNR, load variance, and power consumption, the GA method shows the same value in each repetition. It is different from ACO and PSO that show varying values. Finally, the selection of the path pairs by the GA method indicates the pairs of the path that are always the same as by the ACO and PSO methods indicate those that vary.

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Section: Ad Hoc Network and Scalarizationmentioning

confidence: 99%

Section: Ad Hoc Network and Scalarizationmentioning

confidence: 99%

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The Characteristics of Metaheuristic Method in Selection of Path Pairs on Multicriteria Ad Hoc Networks

Gunantara

Putra

2019

Journal of Computer Networks and Communications

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“…Metode ini mampu menghasilkan penyelesaian yang baik untuk menemukan solusi yang optimal, dalam waktu cepat (acceptable). Artificial Bee Colony (ABC) adalah pendekatan population-based metaheuristic diusulkan oleh Karaboga yang terinsiprasi dari perilaku cerdas kawanan lebah madu mencari makanan [3] [4].…”

Section: Pendahuluanunclassified

Optimasi Titik Interkoneksi Distributed Gener-Ation (Pltm Muara) Guna Meminimalkan Rugi – Rugi Daya Menggunakan Metode Artificial Bee Colony (Abc) Pada Penyulang Panji

Supartana¹,

Hartati²,

Sukerayasa³

2018

SPEKTRUM

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Distributed Generation (DG) is a small power plant that can increase realibility, voltage profil, and reduce power losses in distribution network. DG interconnection locations that are less suitable can in/crease power losses. A possibility that can be done to reduce these power losses is by optimizing DG interconnection points. Optimization of the DG interconnection points on the feeder of Panji aims to minimize power losses, where the initial power losses occur at 48.2 kW. Optimization technique is using the Artificial Bee Colony (ABC) method with losses after simulation at 32.263 kW. When compared with the conditions before and after optimization there is a differ-ence in power losses of 16.035 kW, to a decrease in power losses of 33.2% from the previous loss.

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“…Metode optimasi digunakan untuk mencari solusi dari suatu permasalahan seperti, PSO diterapkan pada jaringan ad hoc nirkabel dalam pemilihan pasangan lintasan [4]. Optimasi menggunakan Genetic Algorithm (GA) untuk menentukan Rute pasangan lintasan yang optimal melalui multi-kriteria pada jaringan ad hoc [5].…”

Section: Pendahuluanunclassified

Optimasi Penempatan Distributed Generation Pada Penyulang Goa Lawah Menggunakan Metode Particle Swarm Optimization (Pso)

Negara¹,

Utama²,

Partha³

2018

SPEKTRUM

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Distributed Generation (DG) is a small-scale power plant located close to the center of load. Goa Lawah feeder is a broadcast that is close to the potential of DG namely the Mini Hydro Power Plant on the Unda River in Klungkung Regency. In this research the optimization of Distributed Generation placement to Goa Lawah feeder. Optimization of Distributed Generation placement aims to reduce the value of loss of power that exist in the feeder Goa Lawah. The results of the research obtained at the point of bus 123 by Distributed Generation placement using Particle Swarm Optimization (PSO) method, with power loss 41 kW (44%). The initial loss before the Distributed Generation interconnection of 72 kW after the Distributed Generation interconnection to 31 kW.

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Multi-Criteria Weights on Ad Hoc Networks Using Particle Swarm Optimization for Optimal Path Pairs

Cited by 6 publications

References 0 publications

The Characteristics of Metaheuristic Method in Selection of Path Pairs on Multicriteria Ad Hoc Networks

The Characteristics of Metaheuristic Method in Selection of Path Pairs on Multicriteria Ad Hoc Networks

Optimasi Titik Interkoneksi Distributed Gener-Ation (Pltm Muara) Guna Meminimalkan Rugi – Rugi Daya Menggunakan Metode Artificial Bee Colony (Abc) Pada Penyulang Panji

Optimasi Penempatan Distributed Generation Pada Penyulang Goa Lawah Menggunakan Metode Particle Swarm Optimization (Pso)

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