基于蚁群算法的多约束动态旅游路线规划

Multi-Constraint Dynamic Tourism Route Planning Based on Ant Colony Algorithm

摘要: 现有的路线规划算法大多仅关注性能的改进，而常常忽略了多约束条件的影响，并且当前研究的约束条件往往比较固定，在动态多约束条件下进行路线评价和规划的研究十分必要。为顺应疫情放开后攀升的旅游需求，本文设计并实现基于蚁群算法的多约束条件下的旅游路线规划方案，立足于时间、费用两个固定约束条件和激励收入动态约束条件，探究变化的多约束条件对旅游路线规划的影响。该方案成功规划旅游产业集聚的长三角地区旅游路线，避免旅游路线相似和同质化问题，提供高质量游玩体验，促进长三角地区旅游业发展。

Abstract: Most of the existing path planning algorithms only focus on the improvement of performance, and often ignore the influence of multiple constraints, and the constraints of the current research are often relatively fixed, and it is necessary to conduct path evaluation and planning under dy-namic multi-constraint conditions. In order to meet the rising tourism demand after the epidemic liberalization, this paper designs and implements a tourism route planning scheme under dynamic constraints based on ant colony algorithm, based on the two fixed constraints of time and cost and the dynamic constraints of incentive income, and explores the impact of changing multiple constraints on tourism route planning. The plan successfully plans the tourism routes in the Yangtze River Delta region where the tourism industry is clustered, avoids the problem of similarity and homogeneity of tourist routes, provides high-quality play experience, and promotes the development of tourism in the Yangtze River Delta region.