Scheduling method based on single employee competent to multiple jobs

Abstract

The invention discloses a scheduling method based on a single employee competent to multiple jobs. According to the method, a high-precision business volume prediction result is obtained through a machine learning model, a business volume prediction model is modified with significant factors taken into account, and the model precision is improved. The multiple jobs of a task are decomposed based on a queuing theory, an optimized genetic algorithm is used to satisfy the scheduling constraints of a single employee with multiple jobs and company labor regulations, and thus, a humanized schedulingresult is obtained. Based on the transformation of the human distribution pattern, the managers are liberated from the heavy scheduling work, the scheduling result is more fair and just, and the employees' enthusiasm for work is improved. Moreover, an intelligent human distribution system improves the service perception and satisfaction of customers.

Description

technical field [0001] The invention relates to the field of intelligent management of human resources, in particular to a shift scheduling method based on the simultaneous competence of a single employee for multiple positions. Background technique [0002] With the quantitative management of human resources, the demand for forecasting the business volume of the operation center is increasing, and at the same time, the requirements for service level, seat utilization and man-hour management are constantly improving. Under the current conditions, how to rationally arrange manpower, improve business processing efficiency, and optimize on-site management has become a huge challenge. A scientific and reasonable business forecasting model is an important basis for rationally arranging shift schedules, and an important link for the operation center to achieve high-efficiency operation management, reduce operating costs, and ensure the quality and level of customer service. [00...

AI Technical Summary

Problems solved by technology

The existing shift scheduling method has a scheduling lag, and there is no pre-evaluation of the personnel requirements of each position per hour, resulting in a lag in personnel scheduling and affecting the task processing efficiency of the operation platform

Failure to take into account the increase in demand for post personnel due to business growth, especially during peak periods, based on past experience may lead to overtime business processing time; failure to consider post issues, resulting in unbalanced distribution of post personnel during a certain period of time, and some post personnel are too surplus , and the problem that the personnel in some posts are too tense

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