Research on Planning and Path Optimization of Leisure Sports Activities based on Multi-objective Genetic Algorithm

Abstract

Recreational sports are essential for boosting physical health and improving quality of life. The goal of this research is to optimize the planning of leisure sports by presenting a new method based on a multi-objective genetic algorithm. Acknowledging the intricacy of organizing recreational sports events, we suggest an approach that concurrently maximizes several goals, such as the use of resources, player happiness, and ecological impact. The topic is first formulated as a multi-objective optimization task in the paper, and a genetic algorithm is used to handle the objectives’ inherent conflict. With its ability to effectively explore the solution space, the genetic algorithm produces a set of Pareto-optimal solutions that show trade-offs for the conflicting goals. The integration of several factors, including time preferences, geographical limitations, and environmental sustainability, guarantees a thorough and equitable strategy for leisure sports scheduling. In the area of leisure sports planning, the use of a multi-objective genetic algorithm offers a reliable solution that can be tailored to meet various circumstances and goals. As the need of encouraging healthy lifestyles becomes more widely acknowledged, this research offers a useful tool for maximizing the organization and performance of recreational sports activities, enhancing the overall wellbeing of people and communities.