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With the continuous development of our country’s economy and the gradual upgrading of the market consumption structure,customer demand for products has gradually shifted from the previous batch to individualization.Traditional large-scale processing and manufacturing can no longer meet the market’s requirements for product individuation,customization,and timeliness.Thus,more and more companies are turning to a multi-variety,small-batch discrete production model.From a production perspective,the production mode of customized discrete processing often has many orders and discrete processing procedures.It is difficult to formulate scientific and reasonable production scheduling plans by manual methods.Meanwhile,the manual methods may cause many problems such as untimely order production,uneven equipment load distribution,and long waiting time for workpieces.In addition,how to predict the production completion time of orders to the greatest extent,and how to quickly deal with dynamic situations such as equipment failures,rush orders,and order cancellations are also problems that customized discrete processing enterprises need to face.This paper takes the discrete processing enterprise as the background,the formulation of efficient and reasonable production scheduling plans as the target.At the same time,we combined the optimization method of the Non-dominated Sorting Genetic Algorithm II（NSGA-II）,and researched a system called Advanced Planning and Scheduling system（APS）that can formulate useful production plans for the enterprise.Finally,an APS system suitable for customized discrete processing enterprises was designed and implemented.Firstly,this paper studies the theoretical knowledge related to the APS system,expounds the development of APS,points out the defects of ERP（Enterprise Resource Planning）in production scheduling,and discusses the characteristics,constraints,and core aspects of the APS system that is more suitable for production scheduling.Next,the APS optimization theory is summarized.The Job Shop Scheduling Problem and Flexible Job Shop Scheduling Problem and related solving algorithms are analyzed in detail.Secondly,analyze the case enterprises of customized discrete processing type.Explains its current market environment,analyzes the problems in production management and summarizes the production process of the workshop,and summarizes the requirements of the APS system based on the above analysis.Thirdly,an improved NSGA-II algorithm is proposed.Aiming at the shortcomings of traditional algorithms when dealing with Flexible Job Shop Scheduling Problem problems such as customized discrete machining workshops,the NSGA-II algorithm is improved.The algorithm adopts a hybrid initialization method,and the process and machine selection parts adopt targeted crossover and mutation strategies,and use adaptive crossover and mutation operators to improve the performance of the algorithm.Then use the standard data set mk01～mk07 to verify the effectiveness of the algorithm.Finally,the APS system is designed and implemented based on the above research.According to the analysis of the system function requirements of the case company,the front-end function module,data management module,and advanced planning and scheduling module were designed.Using Java and other programming languages to design and develop an APS system suitable for customized discrete processing enterprises and demonstrate the completeness and usability of the system in the last.