img

Wechat

Adv. Search

Gold Science and Technology ›› 2016, Vol. 24 ›› Issue (2): 95-100.doi: 10.11872/j.issn.1005-2518.2016.02.095

Previous Articles     Next Articles

Application of NSGA-II in Multi-Objective Route Optimization of Under-ground Mine’s Transportation

TAN Qiren,WANG Liguan,ZHONG Deyun   

  1. School of Resources and Safety Engineering,Central South University,Changsha   410083,Hunan,China
  • Received:2015-04-22 Revised:2015-07-07 Online:2016-04-28 Published:2016-05-30

Abstract:

In order to improve the efficiency of underground mine’s transportation,the running route and distance of electric locomotive must be considered for comprehensive analysis.Under the premise of considering the transportation task of every-shift,a multi-objective route optimization model was proposed with the total amount and the total haul distance of electric locomotive as the optimization goal.The NSGA-II is a commonly used algorithm to solve the problem of multi-objective optimization,it was applied to optimize the route of underground mine’s transportation for the first time,and MATLAB software was used for emulating the solving process.The results show that the best transportation route is quickly gotten by using this method, and it provides basis and assurance for the route arrangement of mine’s transportation.Taking a copper mine in Yunnan Province as an example,the total amount is 1 348.4 t·km and the total haul distance is 2 995.7 m when in the best transportation route.

Key words: NSGA-II, multi-objective optimization, underground transportation, route determination

CLC Number: 

  • TD52 

[1] 祝军.里伍铜矿井下运输系统改造方案优化选择[J].采矿技术,2010,10(4):36-37
[2] 邱福胜,尹春伟,刘成杰,等.新型遥控刮板式放矿机设计及应用[J].黄金科学技术,2014,22(2):67-69.
[3] 杜学武.优化井下运输系统对矿井效益改进研究[J].科技       传播,2010,(8):91,96.
[4] 周科平,翟建波.改进蚁群算法在地下矿山运输路径优化的应用[J].中南大学学报(自然科学版),2014,(1):256-261.
[5] 华臻,王振翀.蚁群优化算法在矿井中的应用[J].煤炭学报,2008,33(3):353-356.
[6] 黄光球,桂中岳.地下矿开拓运输系统优化的遗传算法[J].有色矿冶,1997(3):7-12.
[7] 李玥.基于多目标遗传算法的航空发动机多目标优化控制[D].南京:南京航空航天大学,2007.
[8] 李莉.基于遗传算法的多目标寻优策略的应用研究[D].无锡:江南大学,2008.
[9] 马小姝,李宇龙,严浪.传统多目标优化方法和多目标遗传算法的比较综述[J].电气传动自动化,2010,32(3):48-50.
[10] 孔民秀,陈琳,杜志江,等.基于NSGA-II算法的平面并联机构动态性能多目标优化[J].机器人,2010,32(2):271-277.
[11] Rosenberg R S.Simulation of genetic populations with biochemical properties[D].Ann Harbor:University of Michigan,1967.
[12] 孟红云.多目标进化算法及其应用研究[D].西安:西安电子科技大学,2005.
[13] 杨夏雯.多目标进化算法的改进及其应用研究[D].南京:南京航空航天大学,2012.
[14] 崔逊学.多目标进化算法及其应用[M].北京:国防工业出版社,2008:55-57.
[15] 罗斌.基于NSGA-II的含风电场电力系统多目标调度计划研究[D].长沙:长沙理工大学,2013.
[16] 谢文君.多目标遗传算法在煤气化过程中的应用[D].西安:西安科技大学,2013.
[17] 谈恩民,王鹏.基于NSGA-Ⅱ算法的SoC测试多目标优化研究[J].电子测量与仪器学报,2011,25(3):226-232.

No related articles found!
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!