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Application of Multi Objective Optimization in Prioritizing and Machine Scheduling: A Mobile Scheduler Toolkit

by Sunita Bansal, Manuj Darbari
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International Journal of Applied Information Systems
Foundation of Computer Science (FCS), NY, USA
Volume 3 - Number 2
Year of Publication: 2012
Authors: Sunita Bansal, Manuj Darbari
http:/ijais12-450468

Sunita Bansal, Manuj Darbari . Application of Multi Objective Optimization in Prioritizing and Machine Scheduling: A Mobile Scheduler Toolkit. International Journal of Applied Information Systems. 3, 2 ( July 2012), 24-28. DOI=http:/ijais12-450468

@article{ http:/ijais12-450468,
author = { Sunita Bansal, Manuj Darbari },
title = { Application of Multi Objective Optimization in Prioritizing and Machine Scheduling: A Mobile Scheduler Toolkit },
journal = { International Journal of Applied Information Systems },
issue_date = { July 2012 },
volume = { 3 },
number = { 2 },
month = { July },
year = { 2012 },
issn = { 2249-0868 },
pages = { 24-28 },
numpages = {9},
url = { https://www.ijais.org/archives/volume3/number2/205-0468/ },
doi = { http:/ijais12-450468 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2023-07-05T10:45:26.753361+05:30
%A Sunita Bansal
%A Manuj Darbari
%T Application of Multi Objective Optimization in Prioritizing and Machine Scheduling: A Mobile Scheduler Toolkit
%J International Journal of Applied Information Systems
%@ 2249-0868
%V 3
%N 2
%P 24-28
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper presents a new multi objective algorithm to determine optimal configurations of multi-state, multi-task production systems based on availability analysis. A multi-task production system is one in which different subsets of machines can be used to perform distinct functions or tasks. The performance of a manufacturing system is greatly influenced by its configuration. Availability can be used in the context of multi-task production systems to select a particular configuration that maximizes the probability of meeting a required demand for each specific task, or the expected productivity for each task. A particular configuration may not simultaneously maximize the probability of meeting demand for each of the individual tasks, and thus, the problem is treated as a multi-objective optimization problem. The solution to this problem is a set of promising solutions that provides a trade-off among the different objective functions considered.

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Index Terms

Computer Science
Information Sciences

Keywords

Multi-state Multi-task Manufacturing Systems Performance Availability Feasibility Optimization Priority Scheduling

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