基于粗集复合模糊物元的多产品组合生产目标贴近度研究

发布时间：2018-04-15 17:23

本文选题：粗集理论 + 复合模糊物元　；参考：《运筹与管理》2017年05期

【摘要】：在企业实际生产过程中,产品组合生产配置问题是企业制定生产计划时需要解决的首要问题,为了协助企业处理产品组合生产配置问题,提出了一种基于粗集复合模糊物元的多产品组合生产目标贴近度的方法。该方法以产品与产品之间的内在关系为切入点,运用复合模糊物元确定各指标的从优隶属度,构建粗集理论和熵权法对各产品组合配置的生产目标贴近度研究模型,并运用层次分析法对各产品组合生产目标贴近度进行修正。最后,运用该方法对某企业多产品组合配置方案的生产目标贴近度进行了研究分析。研究结果表明,该模型能够有效挖掘产品与产品与产品间的内在关系,以两产品组合配置问题为例,帮组企业确定了两产品组合最优配置方案,并通过与传统产品组合配置选择方法进行比较,说明该模型能够更加有效地实现企业多产品组合生产管理最优目标并提供决策参考。
[Abstract]:In the actual production process of enterprises, the problem of product combination production configuration is the first problem to be solved when enterprises make production plans. In order to assist enterprises to deal with the problem of product combination production configuration,A method based on rough set complex fuzzy matter-element is proposed to measure the closeness degree of multi-product combination production.This method takes the inherent relationship between product and product as the breakthrough point, uses compound fuzzy matter-element to determine the superior membership degree of each index, and constructs the research model of the production target closeness degree of each product combination configuration by rough set theory and entropy weight method.And use the analytic hierarchy process to modify the closeness degree of each product combination production target.Finally, this method is used to study and analyze the closeness degree of the production target of the multi-product combination configuration scheme of a certain enterprise.The results show that the model can effectively excavate the internal relationship between product and product. Taking the problem of two-product combination configuration as an example, the optimal configuration scheme of two-product combination is determined for the group enterprise.By comparing with the traditional product combination configuration selection method, it is proved that the model can achieve the optimal goal of multi-product combination production management more effectively and provide decision reference.
【作者单位】：河南理工大学能源科学与工程学院;
【基金】：国家自然科学基金资助项目(5127089)
【分类号】：F224;F273

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