Optimal Routes Analysis of Vehicles for Auxiliary Operations in Open-pit Mines using a Heuristic Algorithm for the Traveling Salesman Problem

Boyoung Park, Yosoon Choi, Han-Su Park
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引用次数: 3

Abstract

Abstract This study analyzed the optimal routes of auxiliary vehicles in an open-pit mine that need to traverse the entire mine through many working points. Unlike previous studies which usually used the Dijkstra‘s algorithm, this study utilized a heuristic algorithm for the Traveling Salesman Problem(TSP). Thus, the optimal routes of auxiliary vehicles could be determined by considering the visiting order of multiple working points. A case study at the Pasir open-pit coal mine, Indonesia was conducted to analyze the travel route of an auxiliary vehicle that monitors the working condition by traversing the entire mine without stopping. As a result, we could know that the heuristic TSP algorithm is more efficient than intuitive judgment in determining the optimal travel route; 20 minutes can be shortened when the auxiliary vehicle traverses the entire mine through 25 working points according to the route determined by the heuristic TSP algorithm. It is expected that the results of this study can be utilized as a basis to set the direction of future research for the system optimization of auxiliary vehicles in open-pit mines.
基于旅行推销员问题启发式算法的露天矿辅助作业车辆最优路线分析
摘要针对露天矿辅助车辆需要穿越全矿多个工作点的情况,分析了辅助车辆的最优路线。不同于以往的研究通常使用Dijkstra算法,本研究采用启发式算法求解旅行商问题。因此,可以考虑多个工作点的访问顺序来确定辅助车辆的最优路线。以印尼Pasir露天煤矿为例,分析了一辆辅助车辆的行驶路线,该辅助车辆全程不停车,全程监测工作状态。由此可知,启发式TSP算法在确定最优出行路线方面比直观判断更有效;辅助车辆按照启发式TSP算法确定的路线,通过25个工作点穿越整个矿山,可缩短20分钟。期望本文的研究结果可以作为确定未来露天矿辅助车辆系统优化研究方向的依据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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