UGC Approved Journal no 63975(19)

ISSN: 2349-5162 | ESTD Year : 2014
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Published in:

Volume 10 Issue 1
January-2023
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Published Paper ID:
JETIR2301200


Registration ID:
507120

Page Number

b743-b753

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Title

Optimization of Job Shop Scheduling Performance Measures using Hybrid Approaches

Abstract

The job shop scheduling problem is extremely difficult to solve since it is a strong NP-hard issue. The two most common techniques for addressing JSP are direct and heuristic methods. This study has sought and developed effective hybrid heuristics for dealing with issues of massive scale and producing high-quality answers. The multi-objective optimization takes into account more than one goal. The first goal is to find a set of solutions that are as close as possible to the Pareto-optimal front. The second goal is to come up with as many different solutions as possible. Many problems in the real world have more than one goal, which makes them more interesting to solve. This research has tried to find a solution to this problem of multi-objective optimization. Multi- objective benchmark tasks are used to design and test algorithms for the Hybrid Sheep Flocks Heredity Model and the Artificial Immune System Shifting Bottleneck Algorithm. When compared to the Artificial Immune System Shifting Bottleneck Algorithm and other findings from the literature, the Hybrid Sheep Flocks Heredity Model Algorithm is shown to be an effective tool for tackling multi objective problems issue.

Key Words

SFHM, MULTI-OBJECTIVE OPTIMIZATION, JSP, GA

Cite This Article

"Optimization of Job Shop Scheduling Performance Measures using Hybrid Approaches", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 1, page no.b743-b753, January-2023, Available :http://www.jetir.org/papers/JETIR2301200.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"Optimization of Job Shop Scheduling Performance Measures using Hybrid Approaches", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 1, page no. ppb743-b753, January-2023, Available at : http://www.jetir.org/papers/JETIR2301200.pdf

Publication Details

Published Paper ID: JETIR2301200
Registration ID: 507120
Published In: Volume 10 | Issue 1 | Year January-2023
DOI (Digital Object Identifier):
Page No: b743-b753
Country: bhopal, m.p, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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