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首页> 外文期刊>Reliability Engineering & System Safety >A multi-objective optimization problem for multi-state series-parallel systems: A two-stage flow-shop manufacturing system
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A multi-objective optimization problem for multi-state series-parallel systems: A two-stage flow-shop manufacturing system

机译：多状态串并联系统的多目标优化问题：两阶段流水车间制造系统

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摘要

This research investigates a redundancy-scheduling optimization problem for a multi-state series parallel system. The system is a flow shop manufacturing system with multi-state machines. Each manufacturing machine may have different performance rates including perfect performance, decreased performance and complete failure. Moreover, warm standby redundancy is considered for the redundancy allocation problem. Three objectives are considered for the problem: (1) minimizing system purchasing cost, (2) minimizing makespan, and (3) maximizing system reliability. Universal generating function is employed to evaluate system performance and overall reliability of the system. Since the problem is in the NP-hard class of combinatorial problems, genetic algorithm (GA) is used to find optimalear optimal solutions. Different test problems are generated to evaluate the effectiveness and efficiency of proposed approach and compared to simulated annealing optimization method. The results show the proposed approach is capable of finding optimalear optimal solution within a very reasonable time.
机译：这项研究调查了多状态串联并联系统的冗余调度优化问题。该系统是具有多状态机的流水车间制造系统。每个制造机器可能具有不同的性能速率，包括完美性能，降低的性能和完全故障。此外，考虑热备用冗余以解决冗余分配问题。该问题考虑了三个目标：（1）最小化系统购买成本；（2）最小化制造时间；（3）最大化系统可靠性。通用生成函数用于评估系统性能和系统的整体可靠性。由于该问题属于组合问题的NP难类，因此使用遗传算法（GA）查找最优/接近最优解。产生了不同的测试问题，以评估所提出方法的有效性和效率，并与模拟退火优化方法进行了比较。结果表明，所提出的方法能够在非常合理的时间内找到最优/近最优解。

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