A Parameterization Approach Of Demand-Driven Material Requirements Planning (Ddmrp)

Abstract

This thesis is created to offer a decision support system using Demand-Driven Material Requirements Planning (DDMRP) to minimize the average on-hand inventory levels which is driven by the inefficiency of the current policy. DDMRP has been an emerging inventory management approach that has received significant attention recently. The method introduces the buffer stock to decouple the production chain and reduce the impact of demand fluctuations. However, the performance of DDMRP relies on numerous parameters that affect its efficiency. Therefore, this paper introduces a MILP parameterization model that proposes optimal parameters then presents the production planning DDMRP with objective function of minimizing the average on-hand inventory of buffer stock. The suggested solutions yield significant improvements in minimizing and defining the appropriate stock levels for the case study company and serve well as decision making support.