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Multi-objective design optimisation of repairable k -out-of- n subsystems in series with redundant dependency.

Authors :
Habib, Milia
Yalaoui, Farouk
Chehade, Hicham
Jarkass, Iman
Chebbo, Nazir
Source :
International Journal of Production Research; Dec2017, Vol. 55 Issue 23, p7000-7021, 22p, 2 Diagrams, 11 Charts, 3 Graphs
Publication Year :
2017

Abstract

Several researches have been investigated on Multi-Objective Redundancy Allocation Problems (MORAPs), but none of them have considered the redundant dependency at the design stage. This latter which is a special kind of failure dependency can affect significantly the system performance. Due to this fact, this paper deals with the multi-objective system design optimisation with dependent components by focusing on two objectives: maximisation of system availability and minimisation of system cost with components choice and weight constraints. A system consisting of manyk-out-of-nrepairable subsystems connected in series is considered. The components of a subsystem are supposed to be identical and may be dependent. They are selected from a set of available component types. In addition to the redundancy level and the number of repair teams allocated to each subsystem, the choice of components type and the dependency level are also considered as decision variables. Since the described problem is NP hard, we propose three multi-objective meta-heuristic algorithms based on Non-dominated Sorting Genetic Algorithm (NSGA II) and Strength Pareto Evolutionary Algorithm (SPEA II) with different constraints handling. An exact method is also applied. To analyse their performances, numerical applications are provided and comparisons based on different well-known metrics are presented. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00207543
Volume :
55
Issue :
23
Database :
Complementary Index
Journal :
International Journal of Production Research
Publication Type :
Academic Journal
Accession number :
126454819
Full Text :
https://doi.org/10.1080/00207543.2017.1346319