Abstract: A plurality of desirability prediction values are determined by one or more machine learning models. A desirability prediction value of the plurality of desirability prediction values corresponds to a particular client and a particular product. A plurality of global constraints are determined. A plurality of products are allocated to a plurality of clients based on the plurality of determined desirability prediction values and the plurality of determined global constraints.

Abstract: An article type adjustment approximation value for each physical article type of a plurality of physical article types of limited quantities is predetermined. A determination is made to assign to a selected client among a set of clients, a set of physical article types among the plurality of physical article types. A group of eligible physical article types for the selected client among the plurality of physical article types is identified. Using one or more machine learning prediction models, a desirability prediction value for each physical article type in the group of eligible physical article types is determined. The desirability prediction values are adjusted using the corresponding predetermined article type adjustment approximation value and a corresponding predetermined client adjustment approximation value to determine corresponding adjusted prediction values. The corresponding adjusted prediction values are used to determine the set of physical article types to be assigned to the selected client.