Article Per Year (5 Year)
p-Index From 2019 - 2024
0.23
P-Index
This Author published in this journals
All Journal Jurnal Ilmiah Teknik Industri
Shanty Kusuma Dewi
Industrial Engineering Universitas Muhammadiyah Malang
Industrial & Manufacturing Engineering

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
An Energy-Efficient No Idle Permutations Flow Shop Scheduling Problem Using Grey Wolf Optimizer Algorithm Cynthia Novel Al-Imron; Dana Marsetiya Utama; Shanty Kusuma Dewi
Jurnal Ilmiah Teknik Industri Vol. 21, No. 1, June 2022
Publisher : Department of Industrial Engineering Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/jiti.v21i1.17634

Abstract

Energy consumption has become a significant issue in businesses. It is known that the industrial sector has consumed nearly half of the world's total energy consumption in some cases. This research aims to propose the Grey Wolf Optimizer (GWO) algorithm to minimize energy consumption in the No Idle Permutations Flowshop Problem (NIPFP). The GWO algorithm has four phases: initial population initialization, implementation of the Large Rank Value (LRV), grey wolf exploration, and exploitation. To determine the level of machine energy consumption, this study uses three different speed levels. To investigate this problem, 9 cases were used. The experiments show that it produces a massive amount of energy when a job is processed fast. Energy consumption is lower when machining at a slower speed. The performance of the GWO algorithm has been compared to that of the Cuckoo Search (CS) algorithm in several experiments. In tests, the Grey Wolf Optimizer (GWO) outperforms the Cuckoo Search (CS) algorithm.
Co-Authors Cynthia Novel Al-Imron Dana Marsetiya Utama