基于改进遗传禁忌搜索混合算法的二维矩形件排样问题研究

Research on Two-Dimensional Rectangular Part Layout Problem Based on Improved Genetic Tabu Search Hybrid Algorithm

摘要: 矩形件排样问题在实际生产中占据着很大的份额。本文主要针对矩形件排样问题中的零件定序问题进行研究。并基于此提出了自适应遗传禁忌搜索算法的序列优化方法，以此来提高矩形件的板材利用率。此算法以遗传算法为全局搜索算法，并通过自适应确定选择、交叉、变异算子的方式对其进行了改进。同时，采用禁忌搜索算法对已经进入收敛稳定阶段的种群进行局部搜索。通过此种方法来找到排样最优序列。实验结果表明：遗传禁忌搜索混合算法在提高板材利用率方面具有很好的效果。

Abstract: The layout problem of rectangular parts occupies a large proportion in actual production. In this paper, the problem of part sequencing in rectangular part layout is studied. Based on this, a sequence optimization method of adaptive genetic tabu search algorithm is proposed to improve the utilization rate of rectangular plates. This algorithm takes genetic algorithm as the global search algorithm, and improves it by adaptively determining the selection, crossover and mutation operators. At the same time, the tabu search algorithm is used to locally search the population that has entered the stage of convergence and stability. This method is used to find the optimal nesting sequence. The experimental results show that the hybrid algorithm of genetic tabu search has a good effect in improving the utilization rate of plates.