Generation of Predictive Configurations for Production Planning

We provide a production planning framework for variant rich customized products (such as automobiles, computers), by calculating entirely constructible configuration sets for future customer demands in a novel manner. Most of the established approaches analyse configurations out of historical order banks for estimating the appropriate set of future demands. In the current environment of rapidly changing designs and highly customized products, historical demands cannot easily be extrapolated to capture future market demand and may not even retain future product document restrictions. In this paper, our aim is to generate configuration sets such that (1) they represent customers buying behaviour (derived from configurations produced in the past and sales planning at aggregate level) (2) they are consistent with the product documentation. Configuration generation is formulated as guided search procedures which utilize the Satisfiability framework. Selection of configuration sets for planning is done by a large scale optimization model. We use column generation and other techniques to solve this large scale optimization model.