森林工程2025，Vol.41Issue(3)：595-602,8.DOI:10.7525/j.issn.1006-8023.2025.03.016
基于遗传算法的被动式木窗材下料优化
Optimization of Passive Wooden Window Material Cutting Based on Genetic Algorithm
摘要
Abstract
In the customization process of passive wooden window manufacturing,reducing material waste during frame cutting is key to cost reduction.This problem is modeled as a one-dimensional cutting stock problem.To address the issue of traditional genetic algorithms where the individual encoding method tends to lead to the destruction of cutting pat-terns and low exploration efficiency during iterations,a new individual encoding method is proposed to maintain the in-tegrity of cutting patterns throughout the evolutionary process.Additionally,a heuristic strategy and a correction strategy are introduced for individual correction and population evolution.Simulation results show that for different test cases,the average material utilization rate,excluding the last remnants,exceeds 99%,with some improvements in the length of the last remnants compared to other algorithms.For two sets of real production data from enterprises,the proposed algo-rithm achieves the theoretical lower bound,with average utilization rates(excluding the last remnants)of 99.49%and 99.66%,respectively,outperforming the results of the company's existing software.This demonstrates the algorithm's potential to effectively reduce costs and provide practical solutions in engineering applications.关键词
一维下料问题/遗传算法/启发式算法/种群编码/可用剩余物Key words
One-dimensional cutting stock problem/genetic algorithm/heuristic algorithm/population encoding/us-able leftovers分类
农业科技引用本文复制引用
任长清,武子棋,闫杰,丁星尘,杨春梅..基于遗传算法的被动式木窗材下料优化[J].森林工程,2025,41(3):595-602,8.基金项目
黑龙江省重大成果转化项目(CG23013). （CG23013）
