<p>The modern supply chain faces multiple challenges such as growing environmental concerns and increasing product quality, particularly in industries which dela with deteriorating items. This study introduces a novel framework that incorporates several carbon emission policies into an imperfect production system aimed at reducing deterioration and carbon emissions for a single vendor multiple-buyers supply chain. To enhance the storage conditions on product quality and environmental sustainability, two different kinds of technologies are incorporated: low-carbon and preservation. This study aims to optimize inventory decisions regarding pricing, different types of investments, production rate, inventory cycle time, and the number of production batches in order to maximize supply chain profit and simultaneously reduce emissions. Based on different carbon emission policies four different models are formulated and these problems are solved with the help of different solution algorithms. Due to the nonlinear nature of the formulated models, a metaheuristic optimization technique is incorporated alongside the traditional approach. For better comparative analysis, a numerical example is demonstrated with the help of two different approaches. It can be concluded that the goat search algorithm (GSA) performs better than the traditional approach (TA) for both economically and environmentally. The result shows that the model under without carbon policy, carbon tax, carbon cap-and-trade, and carbon cap-and-offset policy obtained respectively, 6%, 6.78%, 6.14%, and 6% more profit in GSA than TA. Moreover, the supply chain coordination in GSA has produced relatively less carbon and is as low as 2.46%. Finally, sensitivity analysis, managerial insights, graphical illustrations, and conclusions are done to validate the model.</p>