Redundancy allocation problems considering systems with imperfect repairs using multi-objective genetic algorithms and discrete event simulation
This paper considers a multi-objective genetic algorithm (GA) coupled with discrete event simulation to solve redundancy allocation problems in systems subject to imperfect repairs. In the multi-objective formulation, system availability and cost may be maximized and minimized, respectively; the fai...
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| Veröffentlicht in: | Simulation modelling practice and theory Jg. 19; H. 1; S. 362 - 381 |
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| Sprache: | Englisch |
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2011
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| ISSN: | 1569-190X, 1878-1462 |
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| Abstract | This paper considers a multi-objective genetic algorithm (GA) coupled with discrete event simulation to solve redundancy allocation problems in systems subject to imperfect repairs. In the multi-objective formulation, system availability and cost may be maximized and minimized, respectively; the failure-repair processes of system components are modeled by Generalized Renewal Processes. The presented methodology provides a set of compromise solutions that incorporate not only system configurations, but also the number of maintenance teams. The multi-objective GA is validated via examples with analytical solutions and shows its superior performance when compared to a multi-objective Ant Colony algorithm. Moreover, an application example is presented and a return of investment analysis is suggested to aid the decision maker in choosing a solution of the obtained set. |
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| AbstractList | This paper considers a multi-objective genetic algorithm (GA) coupled with discrete event simulation to solve redundancy allocation problems in systems subject to imperfect repairs. In the multi-objective formulation, system availability and cost may be maximized and minimized, respectively; the failure-repair processes of system components are modeled by Generalized Renewal Processes. The presented methodology provides a set of compromise solutions that incorporate not only system configurations, but also the number of maintenance teams. The multi-objective GA is validated via examples with analytical solutions and shows its superior performance when compared to a multi-objective Ant Colony algorithm. Moreover, an application example is presented and a return of investment analysis is suggested to aid the decision maker in choosing a solution of the obtained set. |
| Author | Droguett, Enrique López Lins, Isis Didier |
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| Keywords | Multi-objective genetic algorithm Redundancy allocation problems Imperfect repair Maintenance Reliability |
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| SubjectTerms | Algorithms Allocations Computer simulation Genetic algorithms Imperfect repair Maintenance Mathematical models Multi-objective genetic algorithm Redundancy Redundancy allocation problems Reliability Repairing |
| Title | Redundancy allocation problems considering systems with imperfect repairs using multi-objective genetic algorithms and discrete event simulation |
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