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1.中国电信股份有限公司广州分公司,广东 广州 510620
2.马晓亮劳模和工匠人才创新工作室,广东 广州 510620
3.中数通信息有限公司,广东 广州 510630
[ "李芳(1975- ),女,中国电信股份有限公司广州分公司客服部副总经理," ]
[ "马晓亮(1973- ),男,博士,中国电信股份有限公司广州分公司副总经理、正高级工程师,华南理工大学工商管理学院讲席教授,马晓亮劳模和工匠人才创新工作室领衔人,主要研究方向为人工智能、自然语言处理和数据安全保护等。" ]
[ "刘英(1979- ),男,现就职于中国电信股份有限公司广州分公司," ]
[ "李媛(1986- ),女,现就职于中国电信股份有限公司广州分公司," ]
[ "辛盛(1975- ),男,现就职于中数通信息有限公司," ]
收稿日期:2024-07-18,
修回日期:2024-09-11,
纸质出版日期:2024-10-20
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李芳,马晓亮,刘英等.多目标滚动时域优化的数学模型在运营商智能派单中的构建与应用[J].电信科学,2024,40(10):152-162.
LI Fang,MA Xiaoliang,LIU Ying,et al.Construction and application of a multi-objective rolling horizon optimization mathematical model in intelligent dispatching for telecom operators[J].Telecommunications Science,2024,40(10):152-162.
李芳,马晓亮,刘英等.多目标滚动时域优化的数学模型在运营商智能派单中的构建与应用[J].电信科学,2024,40(10):152-162. DOI: 10.11959/j.issn.1000-0801.2024224.
LI Fang,MA Xiaoliang,LIU Ying,et al.Construction and application of a multi-objective rolling horizon optimization mathematical model in intelligent dispatching for telecom operators[J].Telecommunications Science,2024,40(10):152-162. DOI: 10.11959/j.issn.1000-0801.2024224.
随着电信行业的迅猛发展,智能派单已成为运营商提升服务质量和效率的关键手段。然而,传统的派单方法难以同时满足运营商对服务效率和服务质量的多重需求。提出了一种基于多目标优化的数学模型,设定了3个主要目标:客户满意度预期总得分、工单响应时间和坐席人员工作负荷平衡。同时设计了一种基于自适应多目标优化算法,结合自适应权重调整、多目标优化和滚动时域优化等技术,求解该多目标优化模型。某省会运营商坐席实验结果表明,该模型能够提升电信运营商的服务效率和服务质量。
With the rapid development of the telecommunications industry
intelligent dispatching has become a key means of enhancing service quality and efficiency for operators. However
traditional dispatching methods struggle to simultaneously meet the multiple demands of operators for service efficiency and quality. A mathematical model based on multi-objective optimization was proposed
which was set with three objectives: total expected customer satisfaction score
work order response time
and agent workload balance. Additionally
an adaptive multi-objective optimization algorithm was designed
incorporating techniques such as adaptive weight adjustment
multi-objective optimization
and rolling horizon optimization to solve the multi-objective optimization model. Experimental results from a provincial telecom operator's agent system demonstrate that the model can improve both the service efficiency and service quality of telecom operators.
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