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Study on Optimization of Coal Truck Flow in Open-Pit Mine

Author(s):

Medium: journal article
Language(s): English
Published in: Advances in Civil Engineering, , v. 2020
Page(s): 1-13
DOI: 10.1155/2020/8848140
Abstract:

A semicontinuous process system consisting of a single-bucket excavator, truck, crushing station, and belt conveyor is the main coal mining process system of a large-scale hard coal open-pit mine. Through analyzing the coal mining production process, the key issues of coal mining truck flow optimization are obtained. Statistical method of using triangular fuzzy numbers analyzes the key time parameters of coal mining truck flow. Taking one shift, the minimum expected value of number of trucks, as the objective function, the fuzzy expectation of the coal mining semicontinuous process system is established with the constraints of the truck flow continuity at the loading and unloading point, the production capacity of the electric shovel, the production capacity of the crushing station, coal quality, and coal mining production tasks. The truck flow planning model is solved using particle swarm intelligence algorithm. The simulation results show that the result of truck flow planning can effectively reduce truck number, truck dispatching number, transportation costs, and truck queuing. The fuzzy expected truck flow planning model established by the study is suitable for solving the problem of optimizing and matching the production capacity in the process which links electric shovel, truck, and crushing station. It can effectively improve the production efficiency of electric shovel mining, truck transportation, and crushing station.

Copyright: © 2020 Haiming Bao and Ruixin Zhang et al.
License:

This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met.

  • About this
    data sheet
  • Reference-ID
    10426566
  • Published on:
    13/07/2020
  • Last updated on:
    02/06/2021