Parallel Genetic Annealing Algorithm For Solving Circle Piece Blanking Problems

Circle stock process involves aspects of industrial production,which was widely used in platinum,aircraft manufacturing,glass cutting,transformer production and other industries,Circle stock problem is aimed at seeking effective and scientific methods to cut out as many items as possible on the fixed raw materials,increasing material utilization and reducing production cost.There are three studying directions of circle stock problem.The first one is the problem in board,the second one is the problem in coil,and the third is the research on the spheres of the container.At present,the issue of blanking of circle parts is still a hot topic in the whole world.In this paper,the problem of circle stock problem in coils which means placing items with number and size on the indefinite length of the rolling material.The goal is to minimize the length of the rolled material.Therefore,the main work of this article is as follows.(1)An improved placement algorithm is proposed for the layout of circle parts.On the basis of the best position placement algorithm(Best Location Place-BLP),the feasible location search strategy is changed,and the search location is traversed in the upper left part of the circle according to the most left and top principle.Reducing the search feature points to improve the cutting speed of circular parts.The adaptive genetic algorithm is applied to optimize the sequence of circle items.The dynamic genetic operator is introduced to adjust the probability of individual crossover and mutation in the process of population evolution.In the process of evolution,the optimal selection crossover and mutation strategy is adopted to seek the optimal layout sequence.(2)The adaptive genetic algorithm and simulated annealing algorithm are used to solve the circle stock problem.The local search ability of the genetic algorithm is poor,it is easy to fall into the "early maturing" state and affect the final solution quality.Therefore,the simulated annealing algorithm is introduced,and the Portman probability acceptance function is determined by the simulated annealing,so that it has the ability to jump out of the local extremum.The genetic annealing algorithm is applied to solve the problem of circle parts blanking.The fitness function of population is calculated repeat.The time complexity is relatively high.In order to be more suitable for industrial production,a master-slave genetic annealing strategy is adopted to process the individual fitness evaluation process.The placement of items by multiple threads at the same time in order to improve the time performance of the algorithm.(3)Using the JAVA programming language design and development of circle work piece system,through the international data and the reference of the algorithm in the reference literature,the algorithm has a higher rate of material utilization.