Research And Implementation Of Raw Material Intelligent Purchasing System Based On Improved Genetic Algorithm

With the development of China’s social economy,manufacturing industry is growing,and has gradually become one of the important indicators to measure the comprehensive capacity of a country.Nowadays,most manufacturing enterprises adopt information management,which saves manpower and material resources.However,for large equipment manufacturing enterprises,the order-oriented production mode is adopted,and multiple alliance manufacturing enterprises cooperate in production.Only information management can not meet the needs of such enterprises.In terms of raw material procurement,raw materials need unified standards and unified purchase,so large equipment manufacturing enterprises need to adopt centralized procurement management mode to purchase the raw materials required by the manufacturing enterprises in the alliance.In the traditional procurement information management system,the current management of suppliers is only to record the suppliers that meet the procurement standards,and the procurement personnel can not reasonably choose the suppliers with the best comprehensive evaluation of each raw material from the large number of supplier data.Therefore,the need to use information means,intelligent algorithms in the information complex,rich content of many indicators to make a scientific and reasonable choice,effectively realize the centralized procurement management mode of raw materials under the intelligent procurement system,has become the most urgent demand of this kind of manufacturing enterprises.To solve the above problems,this paper researches on the vendor selection problem,before using genetic algorithm to solve the vendor selection problem in the study,the raw material is a one-to-one relationship with suppliers,and the genetic algorithm is easy to premature lead to work out solutions for the local optimal solution,for the existing problems of genetic algorithm is improved.In this paper,a variable weight multi-index multi-constraint mathematical model based on entropy weight method is constructed,and the improved genetic algorithm is used to optimize the solution.As an intelligent algorithm,genetic algorithm can directly use fitness function as search information to measure the degree of excellence of individuals.It does not involve the process of derivation and differentiation.It has the characteristics of good global search ability and high convergence,which can solve such problems well.In this paper,the chromosome coding in the genetic algorithm is designed to realize the situation that one supplier can supply a variety of raw materials.At the same time,adaptive genetic operators are designed for this coding method and the genetic algorithm process is improved,so as to generate the optimal supplier group of raw materials more accurately.The experimental results show that the improved genetic algorithm can effectively avoid the problem of premature convergence of genetic algorithm and improve the precision of decision.For building has the application value of raw material procurement system,this paper studies the mode of procurement management,and then to the centralized purchasing mode to study the composition of raw materials procurement system,according to user requirements analysis can get the system functional requirements and non-functional requirements,and the design of system function in detail.In the aspect of supplier selection,this paper constructs a mathematical model and uses the improved genetic algorithm to solve the problem of supplier decision-making in enterprise procurement,so as to realize a high quality centralized procurement mode of raw material intelligent procurement system.