Robust sustainable sourcing and inventory planning under stochastic carbon emissions
研究多设施企业在多源采购框架下，如何选择不同价格、质量、产能和碳排放的供应商，并制定采购与库存计划，以最小化总成本并满足碳排放监管约束。
In this paper, we study a generalised two-tier supply chain wherein a firm with multiple facilities seeks to select a subset of suppliers with different prices, qualities, capacities, and carbon emissions. Exogenous demand in the second tier then is satisfied by the selected suppliers in a multi-sourcing framework. The firm in our setting seeks to minimise the integrated cost of sourcing, inventory planning, and emission penalties while adhering to operational limitations as well as regulatory constraints. In our setting, we assume that each supplier produces a stochastic amount of greenhouse gas emissions per unit supplied, leading to environmental cost for the sourcing facilities proportionate to the amount sourced. We develop an iterative heuristic coupled with an accelerated Bender's decomposition to solve the underlying NP-hard MINLP robust formulation. First, we demonstrate the superior performance of our methodology against a benchmark commercial solver in terms of both solution quality and run time. Next, utilising data motivated by a real case study, we derive extensive managerial insights with regards to robustness analysis, price of sustainability, and supplier selection. We conclude our analysis by explaining the implications of various parameter settings in practical decision-making.