Optimization of Sports Event Operations Through Algorithmic Scheduling and Management

The operation of sports events requires a highly systematic and refined approach, involving comprehensive planning, scheduling, and resource allocation to meet the needs of participants and spectators while achieving economic and social benefits. For large-scale sports games, the method of diagonal line pass distribution is employed to ensure fairness by preventing athletes from the same unit or with similar performance levels from competing in the same group. This paper proposes an automated arrangement management system that combines the diagonal line pass method with Genetic Algorithms (GA) to optimize the scheduling of track and field events. The algorithm is designed to efficiently manage resources such as tracks, rounds, and competition formats, and it transforms the objective function into a fitness function for optimization. Experimental results demonstrate the improved algorithm's superior performance compared to traditional GA in solving complex scheduling problems, making it a valuable tool for enhancing the efficiency and fairness of sports event management.