Reliability-redundancy Optimization Problem with IntervalValued Reliabilities of Components via Genetic Algorithm
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@Article{JICS-7-284,
author = {Sanat K.M, Laxminarayan Sahoo and Asoke Kumar Bhunia},
title = {Reliability-redundancy Optimization Problem with IntervalValued Reliabilities of Components via Genetic Algorithm},
journal = {Journal of Information and Computing Science},
year = {2024},
volume = {7},
number = {4},
pages = {284--295},
abstract = { This paper deals with the reliability-redundancy optimization problem considering the reliability
of each component as an interval valued number that involves the selection of components with multiple
choices and redundancy levels which maximize the overall system reliability subject to the given resource
constraints arise on cost, volume and weight. Most of the classical mathematical methods have failed in
solving the reliability-redundancy optimization problems because the objective functions as well as
constraints are non-convex in nature. As an alternative to the classical mathematical methods, heuristic
methods have been given much more attention by the researchers due to their easier applicability and ability
to find the global optimal solutions. One of these heuristics is genetic algorithm (GA). GA is a computerized
stochastic search method of global optimization based on evolutionary theory of Darwin: “The survival of the
fittest” and natural genetics. Here we present GA based approach for solving interval valued mixed integer
programming in reliability-redundancy optimization problem with advanced genetic operators. Finally, a
numerical example has been solved and also to study the effects of changes of different GA parameters,
sensitivity analyses have been carried out graphically.
},
issn = {1746-7659},
doi = {https://doi.org/},
url = {http://global-sci.org/intro/article_detail/jics/22635.html}
}
TY - JOUR
T1 - Reliability-redundancy Optimization Problem with IntervalValued Reliabilities of Components via Genetic Algorithm
AU - Sanat K.M, Laxminarayan Sahoo and Asoke Kumar Bhunia
JO - Journal of Information and Computing Science
VL - 4
SP - 284
EP - 295
PY - 2024
DA - 2024/01
SN - 7
DO - http://doi.org/
UR - https://global-sci.org/intro/article_detail/jics/22635.html
KW - Reliability-redundancy optimization, Genetic algorithm, Mixed-integer programming, Interval
mathematics, Interval order relations
AB - This paper deals with the reliability-redundancy optimization problem considering the reliability
of each component as an interval valued number that involves the selection of components with multiple
choices and redundancy levels which maximize the overall system reliability subject to the given resource
constraints arise on cost, volume and weight. Most of the classical mathematical methods have failed in
solving the reliability-redundancy optimization problems because the objective functions as well as
constraints are non-convex in nature. As an alternative to the classical mathematical methods, heuristic
methods have been given much more attention by the researchers due to their easier applicability and ability
to find the global optimal solutions. One of these heuristics is genetic algorithm (GA). GA is a computerized
stochastic search method of global optimization based on evolutionary theory of Darwin: “The survival of the
fittest” and natural genetics. Here we present GA based approach for solving interval valued mixed integer
programming in reliability-redundancy optimization problem with advanced genetic operators. Finally, a
numerical example has been solved and also to study the effects of changes of different GA parameters,
sensitivity analyses have been carried out graphically.
Sanat K.M, Laxminarayan Sahoo and Asoke Kumar Bhunia. (2024). Reliability-redundancy Optimization Problem with IntervalValued Reliabilities of Components via Genetic Algorithm.
Journal of Information and Computing Science. 7 (4).
284-295.
doi:
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