基于多种人口进化算法和可持续发展的创业环境的生态体育旅游
1Science and Technology Department, Hebei Petroleum University of Technology, Chengde, 067000, Hebei, China.
Scientific reports
|September 25, 2025
概括
通过改进的人工鱼群算法优化体育旅游路线,通过平衡时间和成本来增强旅游体验. 这种方法为中国的可持续生态体育旅游发展提供了更好的稳定性和准确性.
科学领域:
- 旅游管理 旅游管理
- 计算智能是一种计算智能.
- 可持续发展 可持续发展 可持续发展
背景情况:
- 生活水平的提高增加了旅游需求,但中国的人口密度和时间限制阻碍了旅游业.
- 体育旅游是中国的一个新兴行业,需要专门的路线规划才能实现增长.
- 有效的旅游路线设计对于提高游客满意度和解决时间/成本问题至关重要.
研究的目的:
- 使用多种人口进化算法优化体育旅游路线.
- 通过考虑时间和成本效益来改善整体旅游体验.
- 评估改进的人工鱼群算法的有效性,用于路线规划.
主要方法:
- 多种人口进化算法用于旅游路线优化.
- 人工鱼群算法 (AFSA) 和改进的AFSA进行了性能比较.
- 路线优化专注于尽量减少游客的旅行时间和成本.
主要成果:
- 与标准的AFSA相比,改进的人工鱼群算法显示了更快的合到局部最佳值 (120次代).
- 改进的算法在路线优化中表现出卓越的融合精度和稳定性.
- 该研究验证了改进的AFSA在体育旅游路线规划中的有效性.
结论:
- 改进的人工鱼群算法有效优化体育旅游路线.
- 这种优化通过满足时间和成本要求来增强旅游体验.
- 该算法支持中国生态体育旅游的可持续发展和管理.
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