一维下料方案的遗传算法优化

Optimization for One-Dimensional Cutting-Stock Problem Based on Genetic

在对一维下料方案数学模型分析的基础上 ,提出了一种基于遗传算法的求解方法 .主要思想是把零件的一个顺序作为一种下料方案 ,并视作组合优化问题来求解 .在求解过程中 ,给出了应用遗传算法求解关键问题的编码、解码方法、遗传算子及适应度函数的定义 ,并根据这一算法开发出一维下料方案的优化系统 .实际应用表明 ,采用该方法求解一维下料方案 ,可提高材料的利用率 。

The one dimentsional cutting problem occurs in many industry processes. Based on genetic algorithm, method for one dimensional cutting stock problem is presented after analyzing the mathematical model. The main idea is to change the solution to an permutation and solve it as a combinative problem. The key methods for applying genetic algorithm, coding, decoding, genefic algorithm operators and fitness definition are given. An optimal system for one dimensional cutting stock problem is developed based on the method. Result shows that the algorithm is valid and efficient.