Abstract
An inventory model is developed for an economic production quantity model with learning in production and screening errors under greenhouse gas emissions. The main contribution of this paper is determining an optimal vendor–buyer inventory policy by accounting quality inspection errors at the buyer's end and learning in production at the vendor's end and also considering the Government's penalty and incentive policies to reduce the emission. The buyer warehouse has limited capacity and there is an upper bound on the purchase of products. Moreover, we consider the ordering cost is reduced by an extra investment. Also to find an optimal policy of the proposed mathematical model, a genetic algorithm is established. Numerical examples and sensitivity analysis are shown to illustrate the models.
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