Optimal production scheduling with customer-driven demand substitution

This paper deals with the production scheduling problem with customer-driven demand substitution. We consider a manufacturing system in a make-to-stock environment which is potentially able to produce a large variety of product options (the so-called long-term product assortment) but, for reasons of capacity and operative limitations, only a subset of those options can be available in stock at the same time (the so-called short-term product assortment). In such a context, typical of fields where high-variety strategies are applied, the first-choice option of the customer could be unavailable at a certain instant of time. In that case, if production is planned by taking demand substitution issues into consideration, other options which are good substitutes will be available, thus increasing the probability that the customer chooses to substitute. The paper proposes two mixed-integer linear programming models (for both the lost sale case and the backorder case) for optimising the production schedule by jointly considering (i) capacity and production constraints, and costs on one hand, (ii) and demand substitution issues on the other hand. An extensive experimental analysis has allowed us to evaluate the models’ behaviour in a variety of operative scenarios and to draw some concluding remarks.