Study On The Optimization Of Personnel Scheduling In Public Places Considering The Risk Of Cross-infection

At present,sudden public health events have smoothly entered the normal prevention and control stage.To meet the public service needs of the people,public places must be open to the outside world and begin to operate,but still cannot relax their vigilance.Therefore,the management of public places,especially the optimization of new personnel scheduling in the context of public health emergencies,is still facing unprecedented challenges to ensure the safety of people’s lives in the new form and consider the risk of cross-infection.In the study of personnel scheduling optimization in public places,there is an antinomy relationship between service quality,labor cost,and employee satisfaction.Therefore,how to balance the relationship between the three is the key and difficult point of public place operation and management under the premise of considering the risk of cross-infection.This paper mainly studies the problem of personnel scheduling in public places,taking public places,employees and users as the main research objects,considering the risk of cross-infection among staff in combination with the background of public health emergencies,and providing a feasible management plan for personnel scheduling in the future when public health emergencies occur again.In this paper,the total operating cost is divided into three parts: the penalty cost for failing to meet employee satisfaction,the labor cost due to slowdown,and the penalty cost for failing to meet user satisfaction.The penalty cost of failing to achieve employee satisfaction is reflected by quantifying the difference between the maximum and minimum total working hours of employees;The labor costs caused by slowdowns are reflected by the phenomenon of slowdowns due to the completion of business in advance;The penalty cost for not achieving user satisfaction is reflected by not completing business processing.At the same time,the mixed integer programming model is established to minimize the total operating cost and the risk of cross-infection by considering the constraints of maximum continuous working days.For small-scale problems,the GUROBI solver is used to solve,and the solution results can be obtained in a short time.For medium and large-scale problems,to speed up the solution speed and improve the solution quality,an intelligent hybrid algorithm of genetic algorithm,variable neighborhood search algorithm,simulated annealing algorithm,and genetic algorithm combined with variable neighborhood search algorithm is designed.In the experiment of solving medium and large-scale cases,the optimization effect and performance of four optimization algorithms are compared.Compared to other optimization algorithms,intelligent hybrid algorithms have better solution accuracy,speed,and stability in medium to large-scale applications.Therefore,it can be explained that the model and the intelligent hybrid algorithms designed are feasible and effective.They can solve the combinatorial optimization model and obtain a set of scientific and reasonable scheduling schemes,which provides a new research idea for personnel scheduling optimization in public places in the context of public health events.