Section Article

The Genetic Algorithm for Operational Improvement
Author(s): Dr. Promila Mehta

Abstract
Optimizing complex systems and processes continues to be a significant problem in the area of operational research. This research examines the use of Genetic Algorithms (GAs) as a reliable method for enhancing operational performance. Genetic Algorithms use the principles of natural evolution to provide a heuristic method for solving optimization issues imitating the process of natural selection. This paper introduces a thorough framework for incorporating Genetic Algorithms (GAs) into operational improvement techniques. It highlights the GAs capability to handle multi-objective optimization adapt to dynamic situations and effectively explore enormous search spaces. The study showcases the use of Genetic Algorithms (GAs) in improving operational efficiency cost reduction and decision-making in different sectors via case studies and simulations. The findings emphasize the potential of the GA as a diverse and strong instrument for tackling intricate operational difficulties offering useful insights for both practitioners and scholars.