The distributed flow shop problem under carbon quota constraints

This study delves into the Distributed Flowshop Scheduling Problem (DFSP) and introduces an innovative Iterative Greedy (IG) algorithm to address the gap in existing research regarding carbon quota constraints. By integrating a carbon quota limit into our model, we aim to minimize the makespan without exceeding predefined energy consumption thresholds. Initially, we employ an enhanced NEH algorithm to produce superior initial solutions, thereby boosting the algorithm's efficiency. Subsequently, we refine the solution's destruction and reconstruction process during the construction phase and introduce a dynamic speed adjustment strategy that adheres to energy consumption limits. This approach not only satisfies carbon quota constraints but also significantly reduces the makespan. Through meticulous parameter calibration and extensive performance evaluations across 720 instances, we validate the efficacy of our proposed IG algorithm in tackling such complex scheduling challenges.