【作者】 张涛；

【导师】 刘雪红；

【作者基本信息】 武汉理工大学 ， 工业工程， 2020， 硕士

【摘要】 近年来,随着制造业的快速发展以及信息化技术日渐普及,传统制造行业面临巨大挑战的同时也迎来了新的机遇。医疗器械行业属于制造业中的大类,在医疗器械产品生产过程中,由于其行业的特殊性,产品必须达到无菌的要求,而灭菌作为产品出厂前的最后一道工艺,是保证产品质量最重要的一环,但在实际生产过程中,由于灭菌处理时间较长,导致在制品库存积压,产品订单频繁拖期问题尤为突出,而且灭菌加工过程能耗较高,对企业生产效益和社会效益造成了极大的影响。本文以医疗器械企业为背景,以灭菌工艺调度为研究对象,针对灭菌工艺生产调度的特点,建立不同容量平行机批调度的多目标优化问题模型,同时,为求解该问题,在多目标进化算法NSGA-Ⅲ的基础上进行改进,提高算法的综合性能,并与该模型结合,进行了算例分析。论文的主要研究内容如下:(1)通过对医疗器械行业背景、灭菌工艺批调度问题的难点和求解方法的分析,对NSGA-Ⅲ算法的相关理论知识进行总结,为下文合理、准确的改进NSGA-Ⅲ算法及建立数学模型,并求解该问题,奠定坚实的理论基础。(2)针对NSGA-Ⅲ算法中,基于参考点的选择策略在一定程度上无法保证种群分布的多样性,最终导致Pareto解集无法均匀分布于解空间,不仅影响了种群的多样性,还减缓了算法的收敛速度的缺陷,本文提出自适应惩罚距离和自适应邻域思想来改进NSGA-Ⅲ算法,利用基于自适应惩罚距离的自适应邻域删除策略来代替原生NSGA-Ⅲ的小生境保留策略,在该策略中忽略个体所处的Pareto等级层,在选择个体进入下一代时,根据个体邻域以及惩罚距离来删除多余个体,达到保证种群多样性和提高算法收敛速度的目的。通过实验验证,证明改进的NSGA-Ⅲ算法在收敛性和多样性上明显占优。(3)结合医疗器械企业灭菌工艺批调度问题的特点,以准时性、节能性和经济效益为优化目标,建立了灭菌工艺批调度问题数学模型,并将本文提出的NSGA-Ⅲ-ANS算法应用于求解该问题。为了适应该问题求解的需要,重新定义了交叉变异策略,并加入一种局部搜索策略以增强算法的搜索能力。最后,根据某医疗器械企业实际生产情况,设计仿真实验,验证了本文提出的算法在灭菌工艺批调度问题上的应用效果显著。更多还原

【Abstract】 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.更多还原