@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}
}