A novel relational approach for assembly system supply planning under environmental uncertainty

Abstract

We propose a new optimisation approach to address a multi-period, inventory control problem for an assembly system under stochastic environment. Significant drawback in a construction of a real-life model for a multi-product, multicomponent assembly system is the fact that the shortage cost is typically known for a final product while the optimisation is carried out on assembly components. In the cases when the same type of components assemble different types of finished products, this becomes insuperable obstacle for most of the known approaches. In addition, restrictive assumptions about component demand are common for number of published models. Therefore, we develop a framework, which has the ability to incorporate real shortage costs of the final products within the optimisation process and to incorporate more realistic assumptions about product demand. The aim is to define a completely new optimisation approach in the case of complex component's interdependencies in assembly systems. The inclusion of the proposed model in the optimisation process is shown by the example of a known simple stochastic demand model. Simple SQL procedures have been presented which benefits from the relational structure of the problem.