An Intense Examination of Contemporary Decision Support Systems and Sophisticated Optimization Methods

Abstract

This paper examines the progression and incorporation of Decision Support Systems (DSS) and sophisticated optimization approaches. The advancement of technology has led to the evolution of DSS architectures from basic rule-based systems to complex structures that include big data analytics, machine learning, and artificial intelligence. Simultaneously, there has been a notable transformation in optimization strategies, as they have transitioned from conventional methodologies to more flexible and expandable approaches. The integration of decision support systems (DSS) with modern optimization approaches is having a transformative impact on decision-making processes in diverse fields. This integration provides improved efficiency, adaptability, and precision. This study offers a thorough examination of the aforementioned advancements, their practical ramifications, obstacles, and potential avenues for future exploration.