The Design Of Linear Guideway Cutting Problem's Intelligent Optimization Algorithm

Linear sliding guidway(linear guidway)has advantage of least resistance,smooth motion and high precision,so it widely used in CNC machine,precision machinery and electronic processing device,etc.Currently,the linear guideway has been serialized,standardized.For the various needs of customers and the fixed length of raw materials,a reasonable arrangement for cutting plan of raw materials should be made.This arrangement can improve economic efficiency and be significant.Linear guideway cutting issues belong to one-dimensional cutting problem.By consulting a large number of domestic and foreign relevant information on the one-dimensional cutting stock problem,the problem of variable size packing theory and research were reviewed.Considering the hole spacing,loss of cutting,the structure,characteristics and key performance indicators of the linear guideway cutting processes,the process requirements need to analyse.The goal is using least raw materials and producing minimal waste and establish a multi-objective mathematical program of linear guideway cutting.Linear guideway cutting issue is combinatorial optimization problem with variable size packing characteristics,and it is more complex than the general packing.The solutions for the complexity of this paper are designed more expected first heuristic algorithm and genetic simulated annealing algorithm.More than expected first heuristic algorithm pitchs from the end of the length and its own characteristics,taking the excellent use of shorter expected as greedy guidelines.This can get less use of raw material and higher raw material.Genetic simulated annealing algorithm,combined with the characteristics of linear guideway cutting,designed mainly to product arrangements which considering cutting direction of chromosome coding,product unit sequence crossover,and mutation insert for the product.Considering the use of raw materials and the least waste of the allelic variation in fitness minimum function,genetic iteration should be made.To overcome premature for the genetic algorithm coding redundancy problems which caused by the introduction of simulated annealing algorithm,the process of evolution in the evolutionary process and select the appropriate value of smaller echromosome in the genetic algorithm to generate progeny should be improved.Finally,based on Excel,use VBA technology,develop simulation program which has a strong utility,and the simulation results show the feasibility of the two algorithms,effectiveness and practicality.Comparative analysis showed that the genetic simulated annealing algorithm outperforms the heuristic algorithm.