Optimal circular economy index and replenishment decisions in carbon-constrained perishable inventory systems with expiration dates

Abstract

Given the environmental limitations of the traditional linear economic model, which prioritizes profit maximization, an increasing number of firms are transitioning to circular production systems. Initially based on the 3R principles of reduce, reuse, and recycle, the circular economy has, in recent times, evolved into broader frameworks such as 6R and 9R, incorporating additional strategies for sustainability and resource efficiency. This study proposes models for jointly optimizing inventory replenishment and circular economy indicators in perishable inventory systems with expiration dates, under carbon-constrained environments. Specifically, it investigates the impact of stock shortages and emissions policies on system performance. Four distinct inventory scenarios are analyzed, with the latter two incorporating partially backlogged shortages. To address these scenarios, four customized solution algorithms are developed and validated through computational experiments. For the scenarios involving partial backlogging, sequential quadratic programming is employed as the preferred optimization method. Findings reveal that while carbon cap policies effectively reduce emissions, they also constrain profitability. In addition, price management is a critical determinant of profitability because even marginal increases in unit gross profit can dramatically boost profitability, with the boost being more pronounced in unconstrained cases compared to cases under emission caps. These results underscore the importance of policy-driven incentive mechanisms, such as subsidies for low-emission technologies or the phased tightening of emission caps, in supporting firms to achieving environmental goals without compromising economic viability.