Data Science: Journal of Computing and Applied Informatics
Vol. 7 No. 2 (2023): Data Science: Journal of Computing and Applied Informatics (JoCAI)

On Optimum Sequencing of Job Shop Scheduling in Manufacturing Shop

Nwozo, C.R (Unknown)
Adewoye, S.O. (Unknown)



Article Info

Publish Date
31 Jul 2023

Abstract

Joh shop scheduling problem (JSSP) is an NP Hard problem. The most obvious real-world application of the JSSP is within manufacturing and machining as the parameter description describes. Companies that are able to optimize their machining schedules are able to reduce production time and cost in order to maximize profits. The aim of the problem is to find the optimum schedule for allocating shared resources over time to complete all n jobs within the problem. In this research we employ probability sequencing and make of comparison of job-shop sequencing rule such as first-come, first-served (FCFS) rule, which can be accomplished only by used of digital simulation. The result shown that using probability sequencing, when the machine is free, a job is selected in accordance with a sequencing rule and is allowed to occupy the machine for a time equal to its predetermined processing time. A job is complete when it has been processed through all centers on its route.

Copyrights © 2023






Journal Info

Abbrev

JoCAI

Publisher

Subject

Computer Science & IT

Description

Data Science: Journal of Computing and Applied Informatics (JoCAI) is a peer-reviewed biannual journal (January and July) published by TALENTA Publisher and organized by Faculty of Computer Science and Information Technology, Universitas Sumatera Utara (USU) as an open access journal. It welcomes ...