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中国工业与应用数学学会会刊
主管：中华人民共和国教育部
主办：西安交通大学
ISSN 1005-3085  CN 61-1269/O1
工程数学学报

工程数学学报 ›› 2026, Vol. 43 ›› Issue (3): 495-511.doi: 10.3969/j.issn.1005-3085.2026.03.008cstr: 32411.14.cjem.CN61-1269/O1.2026.03.008

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一种基于混合遗传算法的矿场运输调度方法

闫维纲,   俞潇远,    吴  习   

  1. 上海理工大学能源与动力工程学院，上海 200093
  • 收稿日期:2023-07-29 接受日期:2024-04-18 出版日期:2026-04-15 发布日期:2026-08-15

A Mine Transportation Scheduling Method Based on Hybrid Genetic Algorithm

YAN Weigang,  YU Xiaoyuan,  WU Xi   

  1. School of Energy and Power Engineering, University of Shanghai for Science and Technology, Shanghai 200093
  • Received:2023-07-29 Accepted:2024-04-18 Online:2026-04-15 Published:2026-08-15

摘要：

矿山调度是矿山生产的一个重要方面，其目的是最大限度地提高矿产资源的利用效率，实现最优的生产计划和经营成果。研究了一种基于启发式优化算法的矿山运输调度与规划解决方案。由于矿山运输路径复杂的网络特性，通过参照中国有色金属出版协会出版的《有色金属采矿设计规范》提供的数据构建了一个矿山交通网络图。考虑了各个矿道节点间运输时间、运输油耗及节点采矿和等待的时间，分析了运输路径选择和车辆调度的约束条件，建立了一个追求结构合理、兼顾运输量最大和成本最低的多目标优化模型。使用结合了广度优先搜索算法的Dijkstra算法计算合适的路径，再使用非支配排序遗传算法通过特殊的基因编码方式进行车辆任务分配，并结合熵权法等数学方法来解决卡车自动调度的多目标权重问题。最后经实验模拟，验证了算法对于矿场经营在提高采矿运输量、降低成本、减少浪费时间等方面有积极作用，同时还具有一定的故障调节能力，说明算法的鲁棒性较好。

关键词: 采矿运输, 最优化模型, 混合遗传算法, 基因编码, 矿场路径网络

Abstract:

The mine transportation scheduling planning scheme based on hybrid genetic algorithm is studied. Due to the complex network characteristics of the mine transportation path, a mine transportation network diagram is constructed by referring to the data provided by the Code for Design of Non-ferrous Metals Mining published by China Non-ferrous Metals Publishing Association. Considering the transportation time, transportation fuel consumption, mining and waiting time of each node, the planning model of transportation route selection and vehicle scheduling was established. According to this model, Dijkstra algorithm based on greedy algorithm and non-dominated sorting genetic algorithm are combined to optimize a scheduling transportation scheme with reasonable structure, maximum traffic volume and lowest cost. By improving some genetic operators and combining TOPSIS method and other mathematical methods to optimize genetic algorithm, the problem of scheme selection in mineral transportation is solved. The improved algorithm can significantly increase the amount of mining transportation, reduce the cost and reduce the waste of time.

Key words: mining and transportation, optimization model, hybrid genetic algorithm, gene coding, mine path network

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