| In recent years,with the rapid development of the manufacturing industry and the increasing popularity of information technology,the traditional manufacturing industry is facing great challenges but also ushered in new opportunities.Medical device industry belongs to the categories of manufacturing,in the process of medical equipment production,due to the particularity of the industry,products must meet the requirements of sterile,and sterilization,as the last process before products factory,is the most important part of product quality,but in the actual production process,because of the sterilization process for a long time,resulting in products inventory backlog,product order frequent tardiness problem is particularly prominent,and the sterilization process energy consumption is higher,to the enterprise production caused great impact and social benefits.Based on medical device company as the background to the sterilization process scheduling as the research object,according to the characteristics of the sterilization process production scheduling,establish different capacity of parallel machine scheduling model of multi-objective optimization problem at the same time,in order to solve the problem,multi-objective evolutionary algorithms in the NSGA-Ⅲ on the basis of improvement,improve the comprehensive performance of the algorithm,and combined with the model,the numerical example is analyzed.The main research contents of this paper are as follows:(1)Through the analysis of the medical device industry background,difficulties and solution methods of sterilization process batch scheduling problem,the relevant theoretical knowledge of NSGA-Ⅲ algorithm is summarized,which lays a solid theoretical foundation for the following reasonable and accurate improvement of NSGA-Ⅲ algorithm,the establishment of mathematical model,and the solution of this problem.(2)Against the NSGA-Ⅲ algorithm,based on the reference point selection strategy to a certain extent,there is no guarantee that the diversity of the population distribution and eventually lead to Pareto solution set not evenly distributed in the solution space,not only influenced the diversity of population,also slow down the rate of convergence of the algorithm,this paper puts forward the adaptive punishment distance and adaptive neighborhood ideas to improve the NSGA-Ⅲ algorithm,based on the adaptive punishment from adaptive neighborhood deletion policy instead of native NSGA-Ⅲ niche reserved strategy,in the policy ignores the individual’s level of Pareto layer,When selecting individuals to enter the next generation,the redundant individuals are deleted according to the individual neighborhood and the penalty distance,so as to ensure the population diversity and improve the convergence rate of the algorithm.Experimental results show that the improved NSGA-Ⅲ algorithm is superior in convergence and diversity.(3)Considering the characteristics of the batch scheduling problem of sterilization process in medical device enterprises,the mathematical model of the problem is established with the optimization objectives of punctuality,energy saving and economic benefits,and the NSGA-Ⅲ-ANS algorithm proposed in this paper is applied to solve the problem.In order to meet the need of solving the problem,the crossover mutation strategy is redefined and a local search strategy is added to enhance the search capability of the algorithm.Finally,according to the actual production situation of a medical device enterprise,a simulation experiment is designed to verify the application effect of the proposed algorithm on batch scheduling of sterilization process. |
