Open AccessParticle Swarm Optimization to Solve Unrelated Parallel Machine Scheduling Problems
Author(s) -
Farida Pulansari,
M. D. R. Triyono
Publication year - 2021
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/1125/1/012109
Subject(s) - particle swarm optimization , computer science , scheduling (production processes) , mathematical optimization , minification , turnaround time , job shop scheduling , distributed computing , parallel computing , algorithm , mathematics , schedule , operating system
The problem of unrelated parallel machines scheduling is very important in this industry. Scheduling is useful to save company resources, one of which is in terms of time. With minimization of completion time, companies can fulfill it quickly and precisely. Focuses on unrelated parallel machine scheduling problems that depend on sequences aimed at minimizing total turnaround time by considering setup time. This paper presents how unrelated parallel machine scheduling using the particle swarm optimization algorithm approach. The experimental results obtained indicate the optimum value.