Decision-Making Under Uncertainty: Applications of Management Science

Abstract

Decision-making under uncertainty is a critical challenge faced by organizations across various industries. This paper explores the applications of management science in tackling decision-making problems amidst uncertainty. Through a comprehensive review of literature and case studies, this article examines various methodologies and tools employed in management science to enhance decision-making effectiveness. From probabilistic models to simulation techniques, the paper delineates how these approaches aid in analyzing uncertain situations, identifying optimal strategies, and mitigating risks. , it discusses the integration of advanced analytics and artificial intelligence in decision support systems, offering insights into the future directions of management science in addressing uncertainty.