Abstract: In order to study the operational strategies of fresh products in the stochastic demand environment considering incomplete information and carbon emission reduction factors, two distributionally robust optimization models for the case under cap-and-trade regulation and that without considering carbon emission were formulated, respectively, based on the single period stochastic inventory system. The optimal ordering quantities were solved for two models through max-min expected profit criterion and optimization method. The impacts of the standard deviation coefficient and the trading price of unit carbon permit on the order quantity of fresh products, profit and carbon emissions were verified by conducting numerical analysis. The results show that the optimal storage level is determined uniquely to maximize the expected profit of fresh products in the worst distribution case. When compared with the case without considering carbon regulation, cap-and-trade regulation can lead the retailer to achieve higher profit and lower carbon emissions. Moreover, the partial information of the demand has higher effects on the profit under cap-and-trade regulation than that without considering carbon emission.

Key words: cap-and-trade, distributionally robust, newsvendor problem, fresh products