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首页> 外文期刊>Simulation modelling practice and theory: International journal of the Federation of European Simulation Societies >Redundancy allocation problems considering systems with imperfect repairs using multi-objective genetic algorithms and discrete event simulation
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Redundancy allocation problems considering systems with imperfect repairs using multi-objective genetic algorithms and discrete event simulation

机译:考虑具有多目标遗传算法和离散事件模拟的不完善维修系统的冗余分配问题

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摘要

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.
机译:本文考虑了结合离散事件模拟的多目标遗传算法(GA),以解决维修不完善的系统中的冗余分配问题。在多目标制定中,可以分别使系统可用性和成本最大化和最小化。系统组件的故障修复过程由通用更新过程建模。所提出的方法提供了一组折衷解决方案,这些解决方案不仅包含系统配置,而且还包含维护团队的数量。多目标遗传算法通过示例性分析解决方案进行了验证,并且与多目标蚁群算法相比,具有出色的性能。此外,给出了一个应用示例,并提出了投资回报分析,以帮助决策者选择所获得集合的解决方案。

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