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Reseach Article

Scheduling of Flexible Manufacturing System using Genetic Algorithm (Multiobjective): A Review

by Navnikaa Rajan, Srishti Jaiswal, Tanya Kalsi, Vijai Singh
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 86 - Number 19
Year of Publication: 2014
Authors: Navnikaa Rajan, Srishti Jaiswal, Tanya Kalsi, Vijai Singh
10.5120/15102-2678

Navnikaa Rajan, Srishti Jaiswal, Tanya Kalsi, Vijai Singh . Scheduling of Flexible Manufacturing System using Genetic Algorithm (Multiobjective): A Review. International Journal of Computer Applications. 86, 19 ( January 2014), 9-15. DOI=10.5120/15102-2678

@article{ 10.5120/15102-2678,
author = { Navnikaa Rajan, Srishti Jaiswal, Tanya Kalsi, Vijai Singh },
title = { Scheduling of Flexible Manufacturing System using Genetic Algorithm (Multiobjective): A Review },
journal = { International Journal of Computer Applications },
issue_date = { January 2014 },
volume = { 86 },
number = { 19 },
month = { January },
year = { 2014 },
issn = { 0975-8887 },
pages = { 9-15 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume86/number19/15102-2678/ },
doi = { 10.5120/15102-2678 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:04:38.049867+05:30
%A Navnikaa Rajan
%A Srishti Jaiswal
%A Tanya Kalsi
%A Vijai Singh
%T Scheduling of Flexible Manufacturing System using Genetic Algorithm (Multiobjective): A Review
%J International Journal of Computer Applications
%@ 0975-8887
%V 86
%N 19
%P 9-15
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

A flexible, integrated, computer-controlled environment allows the system to react on occurrence of changes, whether predicted or unpredicted. Scheduling machines of varying capabilities in such an environment has always been a difficult task. This work reviews the various approaches applied to the scheduling problem in an FMS. Various genetic algorithm based approaches considering varied objectives and constraints have been studied and analysed to result in a comparative study. For achieving the desired performance in an FMS it is required that a good scheduling system, taking into account the system conditions should generate an optimal schedule at the right time. Genetic algorithm is capable of finding near to optimal solution in a short time although it doesn't guarantee to find an optimal solution.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Scheduling Flexible