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Research Paper | Computer Science and Information Technology | Nigeria | Volume 12 Issue 5, May 2023 | Rating: 5.2 / 10

Application of Branch and Bound and Dynamic Programming in Demand Forecasting for Supply Chain Optimization

Dr. Joe Essien

Abstract: The implementation of inventory optimization tools enables businesses to make precise inventory allocation decisions, such as the categorization of distribution levels based on demand and constraints and the improvement of demand forecasting. Inventory optimization is a vital concern for retail establishments. Supply chain management forecasts have frequently been unreliable and imprecise due to insufficient optimization strategies and inconsistent alignment of information technology with business strategy. This article presents a technique for the formulation of constraints and the justification of demand forecasting optimization. The methodology is implemented by employing a Branch and Bound and Dynamic Programming approach that is compatible with Expert System extensions. Effective administration of business processes entails fostering coordination, presenting a variety of stakeholder perspectives, and facilitating participation and collaboration. These factors are essential for achieving successful results. Using algorithmic models and rapid prototyping approaches, the research identifies the fundamental factors underlying demand fluctuations and forecasts the most beneficial outcomes for demand and supply chain management. This study presents a comprehensive inventory optimization strategy that aims to improve inventory control throughout the entire supply chain. This strategy employs both the Branch and Bound technique and the Dynamic Programming Optimization Methodology as its methodology.

Keywords: Constrained Optimization, Demand Forecasting, Supply Chain, Optimization Methodology, Dynamic Programming

Edition: Volume 12 Issue 5, May 2023,

Pages: 2617 - 2623