Abstract

Supply chain network design (SCND) plays a crucial role in transforming a supply chain sustainable. Recently, various SCND models have been developed especially focusing on carbon footprint reduction. The current study argues that emphasizing only on carbon footprint cannot entirely transform a supply chain sustainable. There are other dimensions (water footprint, solid waste, and social factor), which need to be taken care of for implementing sustainability. Till now, most of the sustainable SCND models have been developed in deterministic conditions, and very few models have been reported in a stochastic environment. To fill the gaps of existing literature, the current study proposes a multi-product and multi-echelon SCND model by addressing carbon footprint, water footprint, solid waste, social sustainability, service level, different transportation modes and inventories in stochastic condition. The study intends to minimize the total cost and estimate the flow of materials across the various echelons of the supply chain. The model considers the demand and capacity as stochastic variables. Further, chance-constrained programming has been used to model the uncertainty of parameters. In the current research, an individual-level chance constraint with right-hand side uncertainty has been adopted. The applicability of the proposed model has been demonstrated with a numerical example and sensitivity analyses have been conducted by changing model parameters, like probability, carbon footprint, water footprint, solid waste, service level, and social factor. The suggested model facilitates decision-maker to estimate the optimum flow of material across the supply chain for delivering materials of predetermined carbon footprint, water footprint, solid waste, social sustainability, and service level. The model helps the manager to implement the sustainability holistically across the supply chain.

Graphic abstract

摘要

供应链网络设计（SCND）在转变可持续供应链中起着至关重要的作用。最近，已经开发了各种SCND模型，特别是致力于减少碳足迹。当前的研究认为仅强调碳足迹并不能完全改变可持续的供应链。还有其他方面（水足迹，固体废物和社会因素），需要加以注意以实现可持续性。到目前为止，大多数可持续的SCND模型都是在确定性条件下开发的，在随机环境中几乎没有模型被报道。为了填补现有文献的空白，当前的研究通过解决碳足迹，水足迹，固体废物，社会可持续性，服务水平，随机条件下的不同运输方式和库存。该研究旨在使总成本最小化，并估计整个供应链各个梯队的物料流。该模型将需求和容量视为随机变量。此外，机会约束编程已用于对参数的不确定性进行建模。在当前的研究中，采用了具有右侧不确定性的个人水平机会约束。通过数值示例证明了所提出模型的适用性，并通过更改模型参数（例如概率，碳足迹，水足迹，固体废物，服务水平和社会因素）进行了敏感性分析。建议的模型可以帮助决策者估算整个供应链中的最佳物料流，以输送预定碳足迹，水足迹，固体废物，社会可持续性和服务水平的物料。该模型可帮助经理在整个供应链中全面实施可持续性。

图形摘要