A fuzzy linear program for optimal allocation of carbon credits in multi-product firms

Net zero commitments put pressure on companies to decarbonize their operations and products with mitigation measures such as improving energy efficiency and reducing fossil fuel use. In addition, carbon dioxide removal credits can be purchased from vendors to credit hard-to-abate emissions. It is necessary to allocate these credits to meet product-specific carbon footprint reduction and cost targets; providing effective model-based support for such decisions is an emerging challenge. A fuzzy linear programming model is developed here to address this research gap. The model is based on an environmentally-extended enterprise input-output model, which allows consistent computation of the carbon footprint and production cost of each product. When credits are purchased from an external vendor and distributed to the firm’s internal operations, both the carbon footprint reduction and the incremental cost propagate through the production system via intermediate streams. The carbon credits are allocated optimally given company-defined carbon footprint reduction targets and incremental cost limits. The model is first demonstrated in a simple pedagogical case study. It is then applied to an industrial case study of a conglomerate producing a suite of electronics hardware and software products; carbon footprints are reduced by 40% with an incremental production cost of less than 1% for most of the products. These examples show how firms can use carbon credits more effectively to decarbonize their product portfolios. • A model is developed for allocating carbon credits in multi-product companies • An enterprise input-output model is embedded within a fuzzy linear program • Changes in carbon footprint and cost reflect the structure of the production system • Carbon credits are distributed based on product-level footprint and cost targets • The model is demonstrated using illustrative decarbonization case studies