The economic department work tasks distribution methodology based on the genetic algorithm

In the context of the rapid digital transformation of business, economic divisions are faced with the need to revise traditional approaches to labor organization. The increasing complexity of business processes and a dynamic competitive environment require the introduction of innovative solutions that can provide a sustainable competitive advantage. This article presents a technique based on the use of genetic algorithms to optimize the distribution of tasks among employees. This approach allows us to achieve a fundamentally new level of management that takes into account both the objective parameters of tasks and employees, as well as the dynamics of changes in the work environment. The key advantage of the proposed methodology is its adaptability: the system is able to quickly respond to changes in priorities, resource availability and other working conditions. The mechanisms of natural selection and genetic combinations ensure a balanced load distribution that takes into account the professional competencies and current employment of employees. This minimizes the risks of overloading individual employees and increases the overall productivity of the team. A special feature of this solution is the combination of automated data analysis with the possibility of expert correction. The manager receives recommendations on the allocation of tasks, while maintaining control over the process and taking into account the informal aspects of the team's work. This approach not only increases the efficiency of tasks, but also helps to create a more harmonious and productive working atmosphere. As a result of the implementation of this methodology, companies can significantly improve their operational performance and successfully adapt to changes in the business environment, which ultimately leads to a strengthening of their market positions.