东北大学学报:自然科学版 ›› 2018, Vol. 39 ›› Issue (1): 20-25.DOI: 10.12068/j.issn.1005-3026.2018.01.005

• 信息与控制 • 上一篇    下一篇

呼叫中心人力资源配置鲁棒规划模型

宫俊1, 贾倩倩1, 张家生2, 于淼3   

  1. (1. 东北大学 信息科学与工程学院, 辽宁 沈阳110819; 2. 东北大学秦皇岛分校 控制工程学院, 河北 秦皇岛066004; 3. 沈阳建筑大学 管理学院, 辽宁 沈阳110168)
  • 收稿日期:2016-08-02 修回日期:2016-08-02 出版日期:2018-01-15 发布日期:2018-01-31
  • 通讯作者: 宫俊
  • 作者简介:宫俊(1972-),男,安徽马鞍山人,东北大学副教授.
  • 基金资助:
    国家自然科学基金资助项目(71271052,71701137).

Robust Program Model of Human Resource Management for Staffing Call Centers

GONG Jun1, JIA Qian-qian1, ZHANG Jia-sheng2, YU Miao3   

  1. 1. School of Information Science & Engineering, Northeastern University, Shenyang 110819, China; 2. School of Control Engineering, Northeastern University at Qinhuangdao, Qinhuangdao 066004, China; 3. School of Management, Shenyang Jianzhu University, Shenyang 110168, China.
  • Received:2016-08-02 Revised:2016-08-02 Online:2018-01-15 Published:2018-01-31
  • Contact: YU Miao
  • About author:-
  • Supported by:
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摘要: 针对现实呼叫中心中顾客到达不确定的问题,建立了基于排队论的离散流体模型,解决了考虑鲁棒性呼叫中心的人力资源配置问题.通过区间数据来表示顾客到达的不确定集,利用可调整鲁棒优化方法的思想,分析了鲁棒优化模型与确定性优化模型的关系.数值试验表明,使用可调整鲁棒参数的鲁棒优化方法减小了呼叫中心到达率不确定性给呼叫中心系统带来的影响;到达率越大,对应的最优的鲁棒参数越大,模型越保守.

关键词: 呼叫中心, 人力资源配置, 鲁棒优化, 到达不确定, 流体模型

Abstract: Considering the problem that the arrival rates of call centers are uncertain, a discrete fluid model was built based on queuing theory, and the human resource allocation problem of staffing call centers was solved with the robustness. The set of uncertain arrival rate was formulated by using interval data, and by adjusting the robust optimization method of adjustable robust parameters to solve the staffing problem, the relationship between robust optimization model and deterministic optimization model was analyzed. Numerical experiments show that, using the robust optimization method with adjustable robust parameters can reduce the impact of random arrival rates on call centers; with the increasing of arrival rates, the corresponding optimal robust parameter will be increased, and the model is more conservative.

Key words: call center, human resource allocation, robust optimization, uncertain arrival, fluid model

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