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作 者:董辉[1] 林文杰 王瑶为 吴祥 张文安[1] Dong Hui;Lin Wenjie;Wang Yaowei;Wu Xiang;Zhang Wenan(College of Information Engineering,Zhejiang Provincial United Key Laboratory of Embedded Systems,Zhejiang University of Technology,Hangzhou 310023)
机构地区:[1]浙江工业大学信息工程学院浙江省嵌入式系统联合重点实验室,杭州310023
出 处:《高技术通讯》2021年第1期40-47,共8页Chinese High Technology Letters
基 金:NSFC-浙江省两化融合联合基金(U1709213);国家自然科学基金(61573319)资助项目。
摘 要:为满足服装企业在生产过程中合理制定多颜色服装裁剪分床计划的需求,提出了一种基于遗传算法的多色服装裁剪分床解耦优化方法。首先通过分析多色服装裁剪分床问题的特点,将实际生产限制量化为约束条件,从而建立了非线性整数规划的优化模型;其次提出一种基于最小二乘法(LS)的解耦策略,结合遗传算法对服装生产误差和投入生产的裁床数量同时优化,在寻优过程中,通过解耦策略将非线性优化问题分解成一系列线性回归子问题,降低了问题的难度,可快速有效地进行求解,从而得到最佳多色裁剪分床方案,减少裁床投入、布料浪费,实现资源利用的最大化;最后针对4个实际生产案例,将该算法与现有方法进行对比,结果表明所提算法的求解精度和运行时间都更优,具有良好的应用价值。To meet the needs of garment enterprises to design flexible cut order planning of multi-color garments(MCOP),a decoupling optimization method of MCOP problem based on genetic algorithm(MCOP-GA)is proposed.Firstly,an optimization model for nonlinear integer programming is presented by analyzing the characteristics of MCOP problem and the production factors are quantified to be its constraints.Secondly,a decoupling strategy based on least square(LS)is proposed,which combines genetic algorithm to simulateneously optimize the output error of garments and the number of cutting machines.During optimization process,the decoupling approach decomposes the nonlinear integer optimization problem into a series of linear regression sub-problems,which simplifies MCOP problem.Therefore,the optimal scheme is quickly obtained to decrease the number of cutting machines and reduce the waste of materials to maximize the utilization of resources.Finally,according to the results of four practical cases,the proposed algorithm achieves a higher level in precision and efficiency than the existing methods.MCOP-GA has good application value.
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