The importance of production planning with uncertain demand

Abstract

The dissertation work explores the integration of stochastic modeling techniques in production planning to address the challenge of demand fluctuations. It highlights the significance of aligning production decisions with uncertain customer demand and operational constraints. The study emphasizes the limitations of traditional deterministic models in handling dynamic market conditions and proposes a multi-stage stochastic modeling framework for optimal production scheduling. By mitigating economic and systemic uncertainties, the research aims to minimize total costs and enhance responsiveness to changing market dynamics. Ultimately, the dissertation advocates for the strategic adoption of stochastic models to gain a competitive edge in modern business environments.