...
首页> 外文期刊>Journal of Intelligent Manufacturing >Two-echelon fuzzy stochastic supply chain for the manufacturer-buyer integrated production-inventory system
【24h】

Two-echelon fuzzy stochastic supply chain for the manufacturer-buyer integrated production-inventory system

机译:制造商-买方集成生产-库存系统的两级模糊随机供应链

获取原文
获取原文并翻译 | 示例
           

摘要

This paper deals with two-echelon integrated procurement production model for the manufacturer and the buyer integrated inventory system. The manufacturer procures raw material from outside suppliers (not a part of supply chain) then proceed to convert it as finished product, and finally delivers to the buyer, who faces imprecise and uncertain, called fuzzy random demand of customers. The manufacturer and the buyer work under joint channel, in which a centralized decision maker makes all decisions to optimize the joint total relevant cost (JTRC) of entire supply chain. In this account, in one production cycle of the manufacturer we determine an optimal multi-ordering policy for the buyer. To be part of this, we first derive the JTRC in stochastic framework, and then extend it in fuzzy stochastic environment. In order to scalarize the fuzzy stochastic JTRC, we use an evaluation method wherein randomness is estimated by probabilistic expectation and fuzziness is estimated by possibilistic mean based on possibility evaluation measure. To derive the optimal policies for both parties, an algorithm is proposed. A numerical illustration addresses the situations of paddy procurement, conversion to rice and fulfillment of uncertain demand of rice. Furthermore, sensitivity of parameters is examined to illustrate the model and algorithm.
机译:本文讨论了制造商和买方集成库存系统的两级集成采购生产模型。制造商从外部供应商(不是供应链的一部分)采购原材料,然后将其转换为成品,最后交付给买方,后者面临不精确和不确定的需求,即客户的模糊随机需求。制造商和买方在联合渠道下工作,在该渠道中,一个集中的决策者可以做出所有决策,以优化整个供应链的联合总相关成本(JTRC)。因此,在制造商的一个生产周期中,我们为买方确定了最佳的多订单策略。为此,我们首先在随机框架中导出JTRC,然后在模糊随机环境中对其进行扩展。为了对模糊随机JTRC进行量化,我们使用了一种评估方法,其中基于可能性评估措施,通过概率期望估计随机性,并通过可能性均值估计模糊性。为了得出双方的最优策略,提出了一种算法。一个数字说明解决了稻米采购,转为大米以及满足不确定的大米需求的情况。此外,检查了参数的敏感性以说明模型和算法。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号