Penyelesaian Masalah Penempatan Fasilitas dengan Algoritma Estimasi Distribusi dan Particle Swarm Optimization

Clicks: 354
ID: 11789
2016
Free PDF
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Popular

Ranked #40 of 92 articles by views in journal of information systems engineering and business intelligence

Most read Least read

Bar heights use a square-root scale.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Sign in to mint
Abstract
Abstrak —Masalah penempatan fasilitas pada garis lurus dikenal sebagai problem Penempatan Fasilitas pada Satu Baris (PFSB). Tujuan PFSB, yang dikategorikan sebagai masalah NP-Complete, adalah untuk mengatur tata letak sehingga jumlah jarak antara pasangan semua fasilitas bisa diminimalisir. Algoritma Estimasi Distribusi (EDA) meningkatkan kualitas solusi secara efisien dalam beberapa pengoperasian pertama, namun keragaman dalam solusi hilang secara pesat ketika semakin banyak iterasi dijalankan. Untuk menjaga keragaman, hibridisasi dengan algoritma meta-heuristik diperlukan. Penelitian ini mengusulkan EDAPSO, algoritma yang terdiri dari hibridisasi EDA dan Particle Swarm Optimization (PSO). Tujuan dari penelitian ini yaitu untuk menguji performa algoritma EDAPSO dalam menyelesaikan PFSB.Kinerja EDAPSO yang diuji dalam 10 masalah benchmark PFSB dan EDAPSO berhasil mencapai solusi optimal. Kata kunci —penempatan fasilitas, algoritma estimasi distribusi, particle swarm optimization Abstract —The layout positioning problem of facilities on a straight line is known as Single Row Facility Layout Problem (PFSB). Categorized as NP-Complete problem, PFSB aim to arrange the layout so that the sum of distances between all facilities’ pairs can be minimized. Estimation of Distribution Algorithm (EDA) improves the solution quality efficiently in first few runs, but the diversity lost grows rapidly as more iterations are run. To maintain the diversity, hybridization with meta-heuristic algorithms is needed. This research proposes EDAPSO, an algorithm which consists of hybridization of EDA and Particle Swarm Optimization (PSO). The objective of this research is to test the performance of EDAPSO algorithm for solving PFSB.  EDAPSO’s performance is tested in 10 benchmark problems of PFSB and it successfully achieves optimum solution. Keywords — facility layout, estimation distribution algorithm, particle swarm optimization
Reference Key
utamima2016penyelesaianjournal Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Amalia Utamima;Angelia Melani Andrian;
Journal journal of information systems engineering and business intelligence
Year 2016
DOI
10.20473/jisebi.2.1.11-16
URL
https://e-journal.unair.ac.id/JISEBI/article/download/1199/1354
Keywords
penempatan fasilitas algoritma estimasi distribusi particle swarm optimization

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

Comments

No comments yet. Be the first to comment on this article.