基于粒子群优化算法的自动排班方法  

AnAutomatic Scheduling Method Based on a Particle Swarm Optimization Algorithm

作　　者：陈丹雅 林晓丽 官培莉 黄丽媛 甘洁冰 黄凡 何秋霞 CHEN Danya;LIN Xiaoli;GUAN Peili;HUANG Liyuan;GAN Jiebing;HUANG Fan;HE Qiuxia(Hainan Power Grid Co.,LTD.Customer Service Center,Haikou,Hainan province 571100)

机构地区：[1]海南电网有限责任公司客户服务中心,海南海口571100

出　　处：《长江信息通信》2024年第9期62-64,共3页Changjiang Information & Communications

摘　　要：由于现有的排班方法员工效率值较低,接听电话量少,为此研究基于粒子群优化算法的自动排班方法。定义状态特征值来描述排班状态,对排班目标进行更新。计算总体排班优化目标,使得初始可行解为每个班次仅包含一个客服人员。使用粒子群优化算法来建立排班优化模型,使各时段当班的客服人数与人力需求情况最大程度地拟合。确定最优排班计划,建立目标函数用来获得偏差最小值,即为最优解,解决客服排班问题。实验结果表明,实验组的员工效率为60方/班次上下,为三个小组的最高效率;8个小组的客服接听电话量均超过了550次,结果符合预期。有效减少人工成本的浪费,提高员工效率。Due to thc existing scheduling method with low staff efficiency and a small number of phone calls,the automatic scheduling method based on particle swarm optimization algorithm is studied.Define the status feature values to describe the scheduling status,and update the scheduling target.The overall scheduling optimization objective is calculated so that the initial feasible solution includes only one customer service staff per shift.The particle swarm optimization algorithm is used to establish the scheduling optimization model,so that the number of customer service staffand manpower demand in cach period are fit to the maximum extent.Determine the optimal scheduling plan,establish the objective function to obtain the minimum deviation valuc,which is the optimal solution to solve thc problem of customer service scheduling.The experimental results show that the staff efficiency of the experimental group is 60 square/shift,which is the highest efficiency of the threc groups;the customer service calls of the 8 groups exceeded 550 times,and the results meet expectations.Effectively reduce the waste of labor costs,improve staff efficiency.

关 键 词：粒子群算法 排班 工作效率 客服人员 

分 类 号：F560[经济管理—产业经济]