A Hybrid Genetic Algorithm/Simulation Approach for Redundancy Optimization with Objective of Maximizing Mean Lifetime and Considering Component Selection

In this paper, we consider a reliability redundancy optimization problem in a series-parallel type system employing the redundancy strategy of cold-standby. The problem consists of two parts component selection and determination of redundancy level of each component—which need to be solved so that t...

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Main Authors:	H. Karimi, A.A. Najafi
Format:	Article
Language:	English
Published:	Ayandegan Institute of Higher Education, 2013-06-01
Series:	International Journal of Research in Industrial Engineering
Subjects:	reliability redundancy allocation problem monte carlo method genetic algorithm means time to failure
Online Access:	http://www.riejournal.com/article_47939_85d652f9ef5f69d3594e134e10009ca8.pdf

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spelling	doaj-f90e524869344a31904df58d3f92eadd2021-09-06T05:42:55ZengAyandegan Institute of Higher Education,International Journal of Research in Industrial Engineering2783-13372717-29372013-06-0122354647939A Hybrid Genetic Algorithm/Simulation Approach for Redundancy Optimization with Objective of Maximizing Mean Lifetime and Considering Component SelectionH. Karimi0A.A. Najafi1Faculty of Industrial and Mechanical Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran.Faculty of Industrial Engineering, K.N. Toosi University of Technology, Tehran, Iran.In this paper, we consider a reliability redundancy optimization problem in a series-parallel type system employing the redundancy strategy of cold-standby. The problem consists of two parts component selection and determination of redundancy level of each component—which need to be solved so that the mean lifetime of the system can be maximized. The redundancy allocation problem is nondeterministic polynomial-time hard and is solved by a combined genetic algorithm - simulation approach. Finally, this algorithm is tested on 33 benchmark problems.http://www.riejournal.com/article_47939_85d652f9ef5f69d3594e134e10009ca8.pdfreliabilityredundancy allocation problemmonte carlo methodgenetic algorithmmeans time to failure
collection	DOAJ
language	English
format	Article
sources	DOAJ
author	H. Karimi A.A. Najafi
spellingShingle	H. Karimi A.A. Najafi A Hybrid Genetic Algorithm/Simulation Approach for Redundancy Optimization with Objective of Maximizing Mean Lifetime and Considering Component Selection International Journal of Research in Industrial Engineering reliability redundancy allocation problem monte carlo method genetic algorithm means time to failure
author_facet	H. Karimi A.A. Najafi
author_sort	H. Karimi
title	A Hybrid Genetic Algorithm/Simulation Approach for Redundancy Optimization with Objective of Maximizing Mean Lifetime and Considering Component Selection
title_short	A Hybrid Genetic Algorithm/Simulation Approach for Redundancy Optimization with Objective of Maximizing Mean Lifetime and Considering Component Selection
title_full	A Hybrid Genetic Algorithm/Simulation Approach for Redundancy Optimization with Objective of Maximizing Mean Lifetime and Considering Component Selection
title_fullStr	A Hybrid Genetic Algorithm/Simulation Approach for Redundancy Optimization with Objective of Maximizing Mean Lifetime and Considering Component Selection
title_full_unstemmed	A Hybrid Genetic Algorithm/Simulation Approach for Redundancy Optimization with Objective of Maximizing Mean Lifetime and Considering Component Selection
title_sort	hybrid genetic algorithm/simulation approach for redundancy optimization with objective of maximizing mean lifetime and considering component selection
publisher	Ayandegan Institute of Higher Education,
series	International Journal of Research in Industrial Engineering
issn	2783-1337 2717-2937
publishDate	2013-06-01
description	In this paper, we consider a reliability redundancy optimization problem in a series-parallel type system employing the redundancy strategy of cold-standby. The problem consists of two parts component selection and determination of redundancy level of each component—which need to be solved so that the mean lifetime of the system can be maximized. The redundancy allocation problem is nondeterministic polynomial-time hard and is solved by a combined genetic algorithm - simulation approach. Finally, this algorithm is tested on 33 benchmark problems.
topic	reliability redundancy allocation problem monte carlo method genetic algorithm means time to failure
url	http://www.riejournal.com/article_47939_85d652f9ef5f69d3594e134e10009ca8.pdf
work_keys_str_mv	AT hkarimi ahybridgeneticalgorithmsimulationapproachforredundancyoptimizationwithobjectiveofmaximizingmeanlifetimeandconsideringcomponentselection AT aanajafi ahybridgeneticalgorithmsimulationapproachforredundancyoptimizationwithobjectiveofmaximizingmeanlifetimeandconsideringcomponentselection AT hkarimi hybridgeneticalgorithmsimulationapproachforredundancyoptimizationwithobjectiveofmaximizingmeanlifetimeandconsideringcomponentselection AT aanajafi hybridgeneticalgorithmsimulationapproachforredundancyoptimizationwithobjectiveofmaximizingmeanlifetimeandconsideringcomponentselection
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A Hybrid Genetic Algorithm/Simulation Approach for Redundancy Optimization with Objective of Maximizing Mean Lifetime and Considering Component Selection

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