基于捕食搜索策略的遗传算法在矩形件优化排样中的研究

Genetic algorithm based on predatory search strategy for rectangular optimal layout

在木材加工业中,会遇到矩形板材的优化切割排样问题,其核心是充分利用板材,使板材利用率达到最高。在基于遗传算法基础上,提出一种基于捕食搜索策略的遗传算法,用以解决前述问题。对编码方式、遗传算子及适应度函数进行设计,并采用改进的最低轮廓线搜索算法对其进行解码以得到最优排布解。仿真试验所用板材规格为1 220 mm×2 440mm,当排样零件总面积与原材料面积相当时,多种型材分割要求下平均板材利用率可达93.425%;当排样零件总面积相比原材料面积较小时,其不同型材零件分配方案的平均板材利用率为83.35%,证明本文算法的科学性,并得出不同型材零件分配总面积应尽量与原板材面积相当的结论。

In the wood processing industry,the problem of optimized cutting and arranging of rectangular plates is encountered.The core is to make full use of the plates to maximize the utilization rate of the plates.Based on the basic genetic algorithm,this paper proposes a genetic algorithm based on predator search strategy to solve the above problems.The coding method,genetic operator and fitness function are designed and decoded by the improved minimum contour search algorithm to get the optimal layout solution.The plate size used in the simulation experiment is 1 220 mm×2440 mm.When the total area of the sampled parts is equivale nt to the raw material a*rea the average plate utilization rate under the various material type division requirements can reach 93.425%;when the total area of the sampled parts is compared with the raw material area In hours,the average sheet utilization rate for different material part distribution schemes is 83.35%.It directly proves the scientific nature of the algorithm,and concludes that the total area of the distribution of different material parts should be as close as possible to the sheet area.