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考虑原料替代的多周期批量生产策略研究

李建斌, 冯巩, 刘腾飞, 杨成, 梅启煌   

  1. 华中科技大学管理学院, 湖北 430074 中国
  • 收稿日期:2024-07-12 修回日期:2025-11-12 接受日期:2026-01-01
  • 通讯作者: 梅启煌
  • 基金资助:
    国家重点研发计划(2023YFB3308301); 国家自然科学基金面上项目(72071085); 华中科技大学人文社科培育项目(数智化决策优化创新团队)(2021WKFZZX008)

Research on Multi-Period Lot-Sizing Problem Considering Raw Material Substitution

  1. , 430074, China
  • Received:2024-07-12 Revised:2025-11-12 Accepted:2026-01-01

摘要: 考虑到生产能力的限制、多周期排产和原料替代等因素时,批量生产问题的复杂性会显著增加。批量生产过程中可能存在多种可替代原料,每种原料的替代方案均会影响生产成本。本文研究一类具有原料替代的多周期批量生产问题,针对此问题构建了混合整数规划模型,并设计了混合自适应大邻域搜索算法进行求解,该算法将自适应大邻域搜索算法框架与 Gurobi求解器相结合,简化了修复算子的设计过程,同时能快速收敛至较高质量的解。此外,本文采用X烟草工业公司2023年1月-2023年8月的生产数据进行算例分析,并将混合ALNS算法与ALNS算法、Gurobi求解器、贪婪算法进行了对比,实验结果验证了本文算法的可行性和有效性,在小规模算例上混合ALNS能求解出和Gurobi精度相同的解,在大规模算例上具有明显的时间优势,同时混合ALNS求解结果较ALNS的平均改善幅度达到了37.73%。最后,通过数值实验,分析了原料替代策略对生产成本、缺货率的影响以及单位原料替代成本对于总成本的影响。实验结果表明原料替代策略能平均节省约23%的生产总成本,减少约26.4%的缺货率。

关键词: 原料替代, 多周期, 批量生产, 混合ALNS算法, 烟草产品

Abstract: The increasing uncertainty in raw material supply and the complexity of multi-period production planning pose significant challenges for manufacturers, particularly in industries like tobacco manufacturing, where material shortages frequently disrupt operations. This study focuses on the multi-period lot-sizing problem with raw material substitution, aiming to minimize total production costs while ensuring production stability. By incorporating substitution strategies, the research addresses the dynamic interplay between production capacity, raw material availability, and substitution costs, offering a practical solution to enhance supply chain resilience. To tackle this problem, a hybrid Adaptive Large Neighborhood Search (ALNS) algorithm is proposed, integrating heuristic techniques with the precision of the Gurobi solver. This approach leverages the strengths of both methods to efficiently navigate the solution space and handle the complex constraints inherent in the problem. Using real-world production data from a tobacco company, the study demonstrates the algorithm’s effectiveness in significantly reducing computational time for small-scale problems while improving solution quality for large-scale cases compared to traditional methods. Additionally, the analysis highlights the substantial benefits of raw material substitution strategies, which, on average, reduce production costs by 23% and stockout rates by 26.4%, ensuring robust and flexible production planning even under varying substitution cost scenarios. This research not only provides a scalable and efficient solution for multi-period lot-sizing problems but also offers valuable insights into the practical application of substitution strategies in dynamic production environments. By bridging theoretical modeling with real-world case analysis, the findings contribute to the broader field of production management and supply chain optimization, offering a robust framework for addressing complex operational challenges in modern manufacturing industries.

Key words: substitution of raw materials, multi-period, lot-sizing problem, hybrid ALNS, tobacco product