简化路径规划模型，让无人机高效完成任务
Optimizing UAV Trajectories via a Simplified Close Enough TSP Approach
- 用近似距离和凸集约束简化数学模型
- 实测表明计算效率提升且解质量不降
- 适合需快速求解的无人机路径规划场景
本文研究了近似足够旅行商问题（Close Enough Traveling Salesman Problem, CETSP）的求解方法。目标是通过重构模型，以欧氏距离的近似值替代精确计算，并简化目标函数。同时，在约束设计中引入凸集结构，带来显著的计算优势。所提方法在真实世界CETSP实例上进行了实证验证，结合分段式CPLEX求解策略，结果表明该方法能有效管理计算资源，且不牺牲解的质量。此外，文章深入分析了所提数学模型的行为特征，提供了对其性能的全面理解。
原文摘要 · Abstract (English)
This article explores an approach to addressing the Close Enough Traveling Salesman Problem (CETSP). The objective is to streamline the mathematical formulation by introducing reformulations that approximate the Euclidean distances and simplify the objective function. Additionally, the use of convex sets in the constraint design offers computational benefits. The proposed methodology is empirically validated on real-world CETSP instances, with the aid of computational strategies such as a fragmented CPLEX-based approach. Results demonstrate its effectiveness in managing computational resources without compromising solution quality. Furthermore, the article analyzes the behavior of the proposed mathematical formulations, providing comprehensive insights into their performance.
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