Joint Optimization Of Production Scheduling And Maintenance For Capacitated Lot-sizing Problem

In the environment of capacitated lot-sizing problem,it is generally difficult to satisfy the three key indicators such as cost,delivery time,and quality that are important to the company.In order to solve such problems,this paper studies the joint optimization of production scheduling and maintenance for capacitated lot-sizing problem.Based on the model of capacitated lot-sizing problem,an integrated optimization model for production scheduling and maintenance was established.The total production cost,holding cost,set-up cost and backorder cost were minimized,and an improved differential evolution algorithm was designed to solve the model.Simulation experiments show that the integrated optimization model is superior to the fixed-cycle preventive maintenance strategy in terms of total production cost,total maintenance cost,failures and maintenance times.Based on this,a multi-objective optimization model was established considering the total cost of production and the completion rate of orders on time,and a multi-objective differential evolution algorithm was designed to solve the model.Manager can set the weights of different objective functions according to the actual production conditions of the company,to obtain the optimal production scheduling plan.On the basis of the above research,the equipment degradation effect and the multi-yield deteriorating were further considered,and the joint optimization of production scheduling and maintenance were studied.Assume equipment degradation process conforms to the linear degradation characteristics,and considering the impact of machine maintenance on product quality,a joint optimization model for production scheduling,maintenance,and product quality was established.This model can be used to determine the optimal preventive maintenance node,production batch size,and processing sequence.The experimental results show that under different equipment load conditions and degradation rate,the model is significantly better than the fixed-cycle maintenance model in terms of total production cost,on-time orders completion rate and yield rate.Finally,the model parameters sensitivity was analyzed.Based on the results of this study,three optimization objectives,namely total production cost,on-time orders completion rate and yield rate,were further considered.The multi-objective optimization problem was studied based on differential evolution algorithm and double-population differential evolution algorithm.The two algorithms were compared and analyzed on the basis of six indicators,number of non-dominated individuals,the error ratio,the generational distance,spacing metric,distance approaching degree evaluation and two set coverage.Finally,an optimal set of production scheduling solutions were provided for manager reference.