Modern Business Decisions Based on Cloud-Based Genetic Algorithms with Unleash Strategic Optimization

The transformational potential of Genetic Algorithms, often known as GAs, in improving numerous essential areas, such as feature selection, portfolio management, job scheduling, and supply chain operations, is investigated. The ultimate objective is to release strategic optimization by using Cloud-Based Genetic Algorithms (CBGAs) in the decision-making processes of contemporary businesses. The primary goal of this project is to demonstrate the effectiveness of the Genetic Algorithm for Feature Selection (GAFS), the Genetic Algorithm for Portfolio Optimization (GAPO), the Genetic Algorithm for Job Scheduling (GAJS), and the Genetic Algorithm for Supply Chain Optimization (GASCO) in improving performance and efficiency. This study is innovative because it takes a thorough look at the many different uses of GAs across important areas. As a result, it provides a complete knowledge of the influence that GAs has on strategy. It tackles scalability and accessibility issues in a novel way by using the cloud-based paradigm. This ensures that the findings have a wider range of application and are easier to put into practice. The findings demonstrate the flexibility and efficacy of CBGAs in dynamically optimizing complex systems and, as a consequence, favorably affecting the choices that are made in contemporary businesses.