Scholarlink

The drone-truck collaborative delivery system has emerged as a promising logistics paradigm with significant potential for improving efficiency. This study formulates a mixed integer programming model for the multi-dropoff flying sidekick traveling salesman problem (MD-FSTSP) to minimize total delivery time. We propose a two-stage optimization algorithm featuring: (1) a list-based adaptive temperature control strategy that improves upon traditional large neighborhood search by enhancing parameter attenuation in generating initial routes; and (2) a drone range-constrained segmentation strategy that decomposes global paths into feasible sub-paths with local search refinements. Experimental validation using TSPLIB benchmark data and parameter sensitivity analysis shows its superior solution accuracy and convergence speed compared to the existing methods.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

A Two-Stage Optimization Algorithm for the Multi-dropoff Flying Sidekick Traveling Salesman Problem

  • 会议论文

  • 发表日期：

    2026年

查看全文
  • Hongrui Ao,
  • Jihui Zhang,
  • Shengzong Chen

摘要

The drone-truck collaborative delivery system has emerged as a promising logistics paradigm with significant potential for improving efficiency. This study formulates a mixed integer programming model for the multi-dropoff flying sidekick traveling salesman problem (MD-FSTSP) to minimize total delivery time. We propose a two-stage optimization algorithm featuring: (1) a list-based adaptive temperature control strategy that improves upon traditional large neighborhood search by enhancing parameter attenuation in generating initial routes; and (2) a drone range-constrained segmentation strategy that decomposes global paths into feasible sub-paths with local search refinements. Experimental validation using TSPLIB benchmark data and parameter sensitivity analysis shows its superior solution accuracy and convergence speed compared to the existing methods.