Complex & Intelligent Systems ( IF 5.8 ) Pub Date : 2021-05-15 , DOI: 10.1007/s40747-021-00326-9 Srikant Gupta , Ahteshamul Haq , Irfan Ali , Biswajit Sarkar
Determining the methods for fulfilling the continuously increasing customer expectations and maintaining competitiveness in the market while limiting controllable expenses is challenging. Our study thus identifies inefficiencies in the supply chain network (SCN). The initial goal is to obtain the best allocation order for products from various sources with different destinations in an optimal manner. This study considers two types of decision-makers (DMs) operating at two separate groups of SCN, that is, a bi-level decision-making process. The first-level DM moves first and determines the amounts of the quantity transported to distributors, and the second-level DM then rationally chooses their amounts. First-level decision-makers (FLDMs) aimed at minimizing the total costs of transportation, while second-level decision-makers (SLDM) attempt to simultaneously minimize the total delivery time of the SCN and balance the allocation order between various sources and destinations. This investigation implements fuzzy goal programming (FGP) to solve the multi-objective of SCN in an intuitionistic fuzzy environment. The FGP concept was used to define the fuzzy goals, build linear and nonlinear membership functions, and achieve the compromise solution. A real-life case study was used to illustrate the proposed work. The obtained result shows the optimal quantities transported from the various sources to the various destinations that could enable managers to detect the optimum quantity of the product when hierarchical decision-making involving two levels. A case study then illustrates the application of the proposed work.
中文翻译:
直觉模糊环境下多目标供应链网络中物流问题多目标优化的意义
确定满足不断增长的客户期望并在限制可控费用的同时保持市场竞争力的方法具有挑战性。因此,我们的研究确定了供应链网络(SCN)中的低效率。最初的目标是以最佳方式为来自具有不同目的地的各种来源的产品获得最佳分配顺序。本研究考虑在两个独立的SCN组中运行的两种类型的决策者(DM),即双层决策过程。第一级DM首先移动并确定运输到分销商的数量,然后第二级DM合理地选择其数量。旨在最大程度降低运输总成本的一级决策者(FLDM)而二级决策者(SLDM)则试图同时最小化SCN的总交付时间,并平衡各种来源和目的地之间的分配顺序。这项研究实现了模糊目标规划(FGP),以解决直觉模糊环境中SCN的多目标问题。FGP概念用于定义模糊目标,建立线性和非线性隶属函数并实现折衷解决方案。一个现实生活中的案例研究用于说明拟议的工作。所获得的结果显示了从各种来源运往各个目的地的最佳数量,这使得管理者在涉及两个级别的分层决策时能够检测到最佳数量的产品。然后,案例研究说明了拟议工作的应用。