摘 要：针对农村客货邮融合运输中客运准时性、货运时效性与车辆能耗的多目标冲突问题，传统基于固定权重的静态优化方法难以适应实时动态需求。本文提出一种基于云端的多任务协同智能决策方法。该方法首先建立包含客运延误、货运超时和能耗成本的多目标优化模型；其次利用云端平台实时采集运营数据，采用多目标进化算法求解帕累托最优解集；最后通过自适应偏好调整机制，根据当前运输状态动态选取均衡的运输方案。仿真结果表明，该方法在多种动态场景下均能获得优于固定权重法的综合性能，为客货邮融合运输提供了有效的全局优化支持。
关键词：客货邮融合；准时性；时效性；多任务协同优化
中图分类号：F252；0221.6 文献标志码：A DOI：10.15917/j.cnki.1006-3331.2026.03.005
Research on a Multi-task Collaborative Optimization Method for Passenger-freight-postal Integrated Transportation
ZHONG Zhikang, YANG Wenxin, HOU Yang, YANG Ting, HUANG Zhengxiang, LIU Dan
Abstract: To address the multi-objective conflicts among service punctuality,freight timeliness,and vehicle energy consumption in rural passenger-freight-mail integrated transportation,conventional static optimization methods based on fixed weights struggle to adapt to real-time dynamic demands.This paper proposes a cloud-based multi-task collaborative intelligent decision-making approach.The method first establishes a multi-objective optimization model that incorporates passenger delay,freight overtime,and energy costs.Second,it leverages a cloud platform to collect operational data in real time and employs a multi-objective evolutionary algorithm to obtain the Pareto optimal solution set.Finally,through an adaptive preference adjustment mechanism,it dynamically selects a balanced transportation scheme according to the current operating status.The simulation results demonstrate that the proposed method achieves superior comprehensive performance compared to the fixed-weight approach under various dynamic scenarios,providing effective global optimization support for passenger-freight-mail integrated transportation.
Key words: passenger-freight-postal integration; punctuality; timeliness; multi-task collaborative optimization
