Research On Scheduling And Optimization Problems Of Real-time Changes In Work Efficiency

With the rapid development of China's social economy and the great abundance of material wealth of society,people's material living standards have been greatly improved,and consumers are also increasingly inclined to buy high-end,personalized and quality products.However,the traditional automated production line mainly realizes the production of single species and large quantities,and this production mode is far from meeting the needs of consumers.In order to solve the production problems caused by changes in demand,and considering the characteristics of high-end,personalized and quality products such as multiple varieties,small batches and random arrival times,companies need to adopt the production method of workbench,arranging operators to work individually,and then sending the produced semi-finished products to the assembly line for short-line assembly according to the process requirements.In the study of traditional job shop scheduling,parameters such as the processing time of jobs,production rate of equipment,and efficiency of employees are usually assumed to be constants.However,in the above production method,the processing time of job is not only affected by the machine and equipment,but also by employee individual factors.For this reason,this paper presents a systematic and in-depth study of scheduling and optimization problems considering learning,forgetting,fatigue and recovery effects.The research work and innovation points of this paper are as follows.First,the scheduling and optimization problem of constant employee efficiency is studied.The energy consumption cost and maintenance cost due to the individual differences of machines and equipment are fully considered,and it is assumed that machines and equipment with the same work rate have different unit usage costs.Under the situation of constant employee work efficiency,the parallel machine scheduling problems that minimizes the maximum delay time considering the cost is studied.First,a mixed integer programming model is developed.Then,a heuristic algorithm based on an improved earliest work schedule priority rule is proposed.Finally,experiments are conducted using a large amount of random data,and the results verify the performance of the proposed algorithm.The proposed model and algorithm achieve the coordination of productivity and energy consumption cost.Second,the scheduling problem of real-time incremental employee productivity considering the learning effect is studied.the scheduling and optimization problems considering the learning effect is studied,taking into account the impact of the learning effect on the employee's work efficiency and assuming that the individual employee's work efficiency is a time-dependent general exponential increment function.First,the calculation of the actual maximum completion time of jobs is given under the limited workload.Then,it is theoretically demonstrated that the shortest processing time first rule,the weighted shortest processing time first rule,and the earliest due date first rule are the optimal algorithms for minimizing the total completion time,the weighted total completion time,and the maximum lateness of jobs respectively.The conclusion provides a new idea and method for the optimal allocation of human resources in the enterprise.Third,the scheduling problem of real-time decreasing employee work efficiency considering fatigue effect is studied.Taking employee work efficiency as the object of study,the effect of employee fatigue on their work efficiency and the employee scheduling and optimization problems considering fatigue effects are studied,assuming that the work efficiency of employee is a time-dependent exponentially decreasing function.From the enterprise's perspective,it is assumed that the employee's work efficiency can be restored to the optimal state within a limited rest period in order to unify management.In this particular case,a mixed-integer programming model is constructed to minimize the cost and maximize the profit of the enterprise,and experiments are conducted using a large amount of stochastic data,and the results verify the feasibility and effectiveness of the proposed model.Fourth,the scheduling problem of increasing and then decreasing employees' work efficiency considering learning and forgetting effects is investigated.Taking the employee's work efficiency as the object of study,we consider both the learning effect and the forgetting effect on the employee's work efficiency,and assume that the individual employee's work efficiency tends to increase linearly over time in its work period and decrease linearly over time in its rest periods,and the individual employee's work efficiency tends to increase exponentially over time in its work period and decrease linearly over time in its rest periods.The actual output of the employees in the one-interruption scenario and,by extension,the actual output of the employees in the multiple-interruption scenario are investigated.The results of the case study provide a quantitative reference for the selection of the production planning scheme.Finally,the scheduling problem of first decreasing and then increasing employee's work efficiency considering fatigue effect and fatigue recovery is investigated.With the number of employee breaks as the decision variable and assuming that the work efficiency of employee tends to decrease exponentially with time in its work period and increase linearly with time in its rest periods,the employee scheduling and optimization problem with the objective function of minimizing the actual maximum completion time is studied.For the small-scale problem,a mixed integer programming model is developed;for the large-scale problem,a heuristic algorithm based on the shortest processing time first rule is designed and experiments are conducted using a large amount of random data,and the results verify the feasibility and effectiveness of the algorithm because the mixed integer programming model is more difficult to obtain the optimal value in a limited time.The proposed model and algorithm provide decision support for employees to develop reasonable work break schedules and ensure the firm implementation and execution of production plans.This dissertation studies the employee scheduling and optimization problems taking employee work efficiency as the research object and combining the learning effect,forgetting effect,fatigue effect and fatigue recovery on employee work efficiency.This is not only beneficial for enterprises to formulate reasonable employee scheduling strategies and improve employee's work efficiency,but also to reduce the cost and improve the profitability of enterprises.