[1]吕晓峰,崔 洋,马 羚,等.基于改进遗传算法的专用物资中转站调度方案研究[J].机械与电子,2026,44(06):25-32.
　LYU Xiaofeng,CUI Yang,MA Ling,et al.Research on the Dispatching Scheme of Special Material Transfer Station Based on Improved Genetic Algorithm[J].Machinery & Electronics,2026,44(06):25-32.
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基于改进遗传算法的专用物资中转站调度方案研究()
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《机械与电子》[ISSN:1001-2257/CN:52-1052/TH]

卷:
44
期数:
2026年06期
页码:
25-32
栏目:
研究与设计
出版日期:
2026-06-27

文章信息/Info

Title:
Research on the Dispatching Scheme of Special Material Transfer Station Based on Improved Genetic Algorithm
文章编号:
1001-2257 ( 2026 ) 06-0025-08
作者:
吕晓峰; 崔 洋; 马 羚; 王丽婷
海军航空大学,山东 烟台 264001
Author(s):
LYU Xiaofeng ;  CUI Yang ;  MA Ling ;  WANG Liting
( Naval Aviation University , Yantai 264001 , China )
关键词:
物资转运调度; 遗传算法; 变邻域搜索; 自适应交叉变异机制
Keywords:
material transfer and scheduling ;  genetic algorithms ;  variable neighborhood search ;  adaptive crossover and mutation mechanism
分类号:
TP18
文献标志码:
A
摘要:
针对专用物资中转站调度的多约束、高动态、强非线性难题,建立以最小化最大完成时间为优化目标、仓库容量与物资类型为核心约束的数学模型,提出融合改进变邻域搜索( IVNS )与自适应交叉变异机制的混合遗传算法( IVNS-AGA )。该算法通过自适应交叉变异机制提升种群多样性与收敛速度,避免传统遗传算法( GA )早熟收敛;结合 VNS 多邻域切换策略,增强复杂约束下的算法鲁棒性。仿真实验与 Wilcoxon 秩和检验结果表明,相较于传统 GA , IVNS AGA 的收敛速度提升 31.17% ,可稳定获得全局最优解,性能差异具有统计学意义( p <0.05 )。
Abstract:
Aiming at the multi constraint , high dynamic and strong nonlinear problems of special material transfer station scheduling , a mathematical model is formulated with the objective of minimizing the maximum completion time and with warehouse capacity and material type as the core constraints.A hybrid genetic algorithm ( IVNS-AGA ) is proposed , which integrates an improved variable neighborhood search ( IVNS ) with adaptive crossover and mutation mechanism.The algorithm employs an adaptive crossover and mutation mechanism to enhance population diversity and convergence speed , while avoiding the premature convergence of traditional genetic algorithm ( GA ) .By incorporating the multiple neighborhood switching strategy of VNS , the algorithm robustness under complex constraints is further strengthened.Simulation experiments and Wilcoxon rank sum test results demonstrate that , compared with the traditional GA , IVNS-AGA improves the convergence speed by 31.17% , reliably obtains the global optimal solution , and yields a performance difference that is statistically significant ( p <0.05 )

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备注/Memo

备注/Memo:
收稿日期: 2026-03-31
作者简介:吕晓峰 ( 1982- ),男,江苏盐城人,副教授,研究方向为航空军械保障、舰载机弹药调度指挥;崔 洋 ( 1991- ),男,河北正定人,硕士研究生,研究方向为智能算法、强化学习和弹药调度,通信作者, E-mail : 577780036@qq.com 。
更新日期/Last Update: 2026-08-26