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作 者:鄢仁秀 董冕 李国志 YAN Ren-xiu;DONG Mian;LI Guo-zhi(College of Management Science,Chengdu University of Technology,Chengdu 610059,China;School of Business Administration,South China University of Technology,Guangzhou 510641,China;Sichuan Kaiyuan Economic Innovation and Development Research Institute,Chengdu 610o95,China)
机构地区:[1]成都理工大学管理科学学院,四川成都610059 [2]华南理工大学工商管理学院,广东广州510641 [3]四川省开元经济创新发展研究院,四川成都610095
出 处:《系统工程》2025年第1期148-158,共11页Systems Engineering
基 金:四川省科技厅软科学研究计划项目(2022JDR0096);四川省科技成果转移转化示范项目(2024ZHCG0015)。
摘 要:基于数字经济时代工业企业组织结构特点,提出价值目标与生产要素优化目标融合的组织方式,建立以数据为运转要素、以价值维度为层次的工业企业组织结构管理模型。基于这一管理模型构建多约束条件下的组织结构优化模型,设计模拟退火算法求解并进行算例分析。针对交货时间与收益的关系、繁忙概率与工作单元数量和服务率之间的关系进行讨论,分析表明:为了满足较早的交货时间,工业企业需要付出更大的成本;当工作单元配置足够时,增加工作单元数量几乎不能降低繁忙概率,但增加服务率可以显著缓解繁忙程度。最后,探讨了价格与最优收益的关系,发现存在最优价格以达到最优收益,且最优价格相较于最大销售收入价格向上扭曲。Based on the characteristics of industrial enterprises'organizational structure in the digital economy era,this paper proposes an organizational method that integrates value objectives and production factors optimization objectives,establishes an industrial enterprise's organizational structure management model with data as the operating element and value dimension as the level.Based on the management model,a multi-constraint organizational structure optimization model is constructed,a simulated annealing algorithm is designed to solve it,and a numerical example is designed.The relationship between delivery time and revenue,and the relationship between busy probability and the number of work units and service rate are discussed.The analysis shows that:in order to meet the earlier delivery time,industrial enterprises need to pay more costs;when the work unit configuration is sufficient,increasing the number of work units can hardly reduce the busyness,but increasing the service rate can significantly reduce the busyness.Finally,this paper explores the relationship between price and optimal revenue,finding that there is an optimal price to achieve optimal revenue,and that the optimal price is upwardly distorted relative to the maximum sales revenue price.
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