为了对呼叫中心(Call Center)的整体性能进行定量优化分析,针对顾客在ACD(AutomaticCall D istributor)中排队时会因不耐烦而放弃等待,服务台(Agents)根据顾客等待队长使用可变服务率,同时考虑服务台发生故障对系统的影响,讨论了不耐烦...为了对呼叫中心(Call Center)的整体性能进行定量优化分析,针对顾客在ACD(AutomaticCall D istributor)中排队时会因不耐烦而放弃等待,服务台(Agents)根据顾客等待队长使用可变服务率,同时考虑服务台发生故障对系统的影响,讨论了不耐烦、可变服务率M/M/S/K+M可修排队模型.采用矩阵几何方法求解,给出解析解和系统稳态性能指标.结果表明:呼叫中心相关参数给定的条件下可以求出最优服务台数;当等待队长大于零时适当提高服务率可以使系统更优化;为了提高系统性能,可以根据系统中平均故障台数这一指标配备备用服务台;适当增加服务台或者中继线可以提高顾客满意度,减少顾客损失率.展开更多
We consider a single server constant retrial queue,in which a state-dependent service policy is used to control the service rate.Customer arrival follows Poisson process,while service time and retrial time are exponen...We consider a single server constant retrial queue,in which a state-dependent service policy is used to control the service rate.Customer arrival follows Poisson process,while service time and retrial time are exponential distributions.Whenever the server is available,it admits the retrial customers into service based on a first-come first-served rule.The service rate adjusts in real-time based on the retrial queue length.An iterative algorithm is proposed to numerically solve the personal optimal problem in the fully observable scenario.Furthermore,we investigate the impact of parameters on the social optimal threshold.The effectiveness of the results is illustrated by two examples.展开更多
文摘为了对呼叫中心(Call Center)的整体性能进行定量优化分析,针对顾客在ACD(AutomaticCall D istributor)中排队时会因不耐烦而放弃等待,服务台(Agents)根据顾客等待队长使用可变服务率,同时考虑服务台发生故障对系统的影响,讨论了不耐烦、可变服务率M/M/S/K+M可修排队模型.采用矩阵几何方法求解,给出解析解和系统稳态性能指标.结果表明:呼叫中心相关参数给定的条件下可以求出最优服务台数;当等待队长大于零时适当提高服务率可以使系统更优化;为了提高系统性能,可以根据系统中平均故障台数这一指标配备备用服务台;适当增加服务台或者中继线可以提高顾客满意度,减少顾客损失率.
基金supported by the National Natural Science Foundation of China(Grant No.11971486)。
文摘We consider a single server constant retrial queue,in which a state-dependent service policy is used to control the service rate.Customer arrival follows Poisson process,while service time and retrial time are exponential distributions.Whenever the server is available,it admits the retrial customers into service based on a first-come first-served rule.The service rate adjusts in real-time based on the retrial queue length.An iterative algorithm is proposed to numerically solve the personal optimal problem in the fully observable scenario.Furthermore,we investigate the impact of parameters on the social optimal threshold.The effectiveness of the results is illustrated by two examples.
