Open-pit truck scheduling optimization method based on SA-CSA

doi:10.16265/j.cnki.issn1003-3033.2023.S2.0022

Abstract

Abstract:

In order to improve the transportation efficiency of open-pit trucks and reduce mining costs for mine enterprises, minimizing the comprehensive cost of open-pit truck transportation scheduling was set as the objective function, and constraints such as ore production, grade balance, and transportation time were considered. The SA method and the CSA were combined, and the SA-CSA algorithm was employed to optimize the scheduling of open-pit trucks. A large-scale open-pit mine was studied, and the optimization results of the SA-CSA with those of the SA algorithm and CSA were compared. The results indicate that the SA-CSA exhibits superior solution accuracy and convergence speed compared with the SA algorithm and CSA.

Key words: simulated annealing (SA) method, crow search algorithm (CSA), SA-CSA, open-pit mine, truck scheduling optimization

CLC Number:

X948

TIAN Feng, TANG Xiaoqian, QIAO Dongqing. Open-pit truck scheduling optimization method based on SA-CSA[J]. China Safety Science Journal, 2023, 33(S2): 176-181.

Figures/Tables 8

Tab.1

Tab.2

Tab.3

Tab.4

Tab.5

Tab.6

Fig.1

Tab.7

References 18

[1]	曹贺. 露天矿山开采技术进展及发展趋势研究[J]. 世界有色金属, 2020, 35(24):58-59.
	CAO He. Progress and development trend of open pit mining technology[J]. World Nonferrous Metals, 2020, 35(24):58-59.
[2]	常永刚. 露天矿运输系统优化与卡车调度问题研究[D]. 沈阳: 沈阳工业大学, 2018.
	CHANG Yonggang. Study on ptimization of transportation system and truck scheduling in the open-pit[D]. Shenyang: Shenyang University of Technology, 2018.
[3]	龙建成, 许鹏, 袁月明, 等. 露天矿生产车辆安排计划优化设计[J]. 工程数学学报, 2003, 20(7):83-89,142.
	LONG Jiancheng, XU Peng, YUAN Yueming, et al. Optimization design of production vehicle arrangement plan for open-pit mine[J]. Journal of Engineering Mathematics, 2003, 20(7):83-89,142.
[4]	戴剑勇, 杨仕教, 古德生. 遗传算法在水泥矿山卡车运输调度系统中的应用[J]. 中国工程科学, 2006, 8(8):77-80,91.
	DAI Jianyong, YANG Shijiao, GU Desheng. The real time optimization research and application for transportation scheduling system about material quarry of cement with genetic and evolutionary algorithm[J]. Engineering Science of China, 2006, 8(8):77-80,91.
[5]	王俊栋, 李宁, 吴亚辉, 等. 基于改进DCW-QPSO算法的露天矿卡车调度优化方法[J]. 金属矿山, 2019, 49(12):156-162.
	WANG Jundong, LI Ning, WU Yahui, et al. Truck scheduling optimization in open pit mines based on improved DCW-QPSO algorithm[J]. Metal Mines, 2019, 49(12):156-162.
[6]	张岸杨. 基于遗传算法的露天矿车辆配置优化[J]. 工业工程, 2010, 13(6):101-104.
	ZHANG Anyang. Genetic algorithm based vehicle scheduling in open pit mines[J]. Industrial Engineering, 2010, 13(6):101-104.
[7]	苏楷, 门飞. 露天矿运输调度问题求解的自适应果蝇优化算法[J]. 金属矿山, 2017, 47(11):172-176.
	SU Kai, MEN Fei. Adaptive fruit fly optimization algorithm for solving open-pit hauling dispatching optimization problem[J]. Metal Mines, 2017, 47(11):172-176.
[8]	林涛, 郝章肖, 冯竞凯. 基于改进乌鸦搜索算法的云计算任务调度研究[J]. 微电子学与计算机, 2020, 37(2):20-24.
	LIN Tao, HAO Zhangxiao, FENG Jingkai. Research on cloud computing task scheduling based on improved crow search algorithm[J]. Microelectronics and Computer, 2020, 37(2):20-24.
[9]	王颖. 基于乌鸦搜索算法的特征选择算法的研究及改进优化[D]. 长春: 吉林大学, 2019.
	WANG Ying. Research and improvement of feature selection algorithm based on crow search algorithm[D]. Changchun: Jilin University, 2019.
[10]	景楠, 胡怡, 韩喜双. 基于ARIMA与LSTM的新冠肺炎网络关注度趋势研究[J]. 中国安全科学学报, 2020, 30(12):37-42. doi: 10.16265/j.cnki.issn 1003-3033.2020.12.006
	JING Nan, HU Yi, HAN Xishuang. Trend of COVID-19 network attention based on ARIMA and LSTM[J]. China Safety Science Journal, 2020, 30(12):37-42. doi: 10.16265/j.cnki.issn 1003-3033.2020.12.006
[11]	门飞, 蒋欣. 求解露天矿低碳运输调度问题的改进灰狼优化算法[J]. 工矿自动化, 2020, 46(12):90-94.
	MEN Fei, JIANG Xin. Improved grey wolf optimization algorithm for solving low-carbon transportation scheduling problem in open-pit mines[J]. Industrial and Mining Automation, 2020, 46(12):90-94.
[12]	周愉峰, 李志, 邹坤. 危险品运输车辆调度的多目标优化[J]. 中国安全科学学报, 2013, 23(4):113-119.
	ZHOU Yufeng, LI Zhi, ZOU Kun. Multi-objective optimization of hazardous materials transportation vehicle scheduling[J]. China Safety Science Journal, 2013, 23(4):113-119.
[13]	赵世杰, 高雷阜, 于冬梅, 等. 基于变因子加权学习与邻代维度交叉策略的改进CSA算法[J]. 电子学报, 2019, 47(1):40-48. doi: 10.3969/j.issn.0372-2112.2019.01.006
	ZHAO Shijie, GAO Leifu, YU Dongmei, et al. An improved CSA algorithm based on variable factor weighted learning and neighborhood dimension crossover strategy[J]. Electronics, 2019, 47(1):40-48.
[14]	肖子雅, 刘升, 韩斐斐, 等. 正弦余弦指引的乌鸦搜索算法研究[J]. 计算机工程与应用, 2019, 55(21):52-59. doi: 10.3778/j.issn.1002-8331.1808-0077
	XIAO Ziya, LIU Sheng, HAN Feifei, et al. Cow search algorithm based on directing of sine cosine algorithm[J]. Computer Engineering and Application, 2019, 55(21):52-59.
[15]	王世华. 城市公共自行车调度关键技术研究[D]. 杭州: 杭州电子科技大学, 2018.
	WANG Shihua. Research on key technologies of urban public bicycle scheduling[D]. Hangzhou: Hangzhou University of Electronic Technology, 2018.
[16]	彭程, 薛伟宁, 黄轶. 露天矿运输问题的模拟退火优化[J]. 中国矿业, 2018, 27(4):138-141.
	PENG Cheng, XUE Weining, HUANG Zhi. Simulated annealing optimization of transportation problems in open-pit mines[J]. China Mining, 2018, 27(4):138-141.
[17]	郭天中. 基于SA-GA算法的露天矿用卡车调度方法的研究[D]. 包头: 内蒙古科技大学, 2015.
	GUO Tianzhong. Research on truck scheduling method for open-pit mine based on SA-GA algorithm[D]. Baotou: Inner Mongolia University of Science and Technology, 2015.
[18]	张媛. 综合成本最小的露天矿卡车低碳调度优化研究[D]. 西安: 西安建筑科技大学, 2020.
	ZHANG Yuan. Low-carbon dispatching optimization of open-pit truck with minimum comprehensive cost[D]. Xi'an: Xi'an University of Architecture and Technology, 2020.

装卸点	铲装点1	铲装点2	铲装点3	铲装点4	铲装点5	铲装点6
卸矿点1	5.615	3.476	4.398	3.657	5.021	4.897
卸矿点2	4.070	2.064	3.389	4.890	5.378	2.968
卸矿点3	4.691	3.468	4.679	6.521	5.276	4.089
卸矿点4	3.746	4.560	3.501	5.609	3.989	3.236

矿石状况	铲装点1	铲装点2	铲装点3	铲装点4	铲装点5	铲装点6
矿石量/万t	0.53	0.50	0.52	0.5	0.55	0.59
平均品位/%	0.12	0.10	0.13	0.11	0.12	0.11

铲装点	最少车辆数
	SA				CSA				SA-CSA
	卸矿点1	卸矿点2	卸矿点3	卸矿点4	卸矿点1	卸矿点2	卸矿点3	卸矿点4	卸矿点1	卸矿点2	卸矿点3	卸矿点4
1	0	3	2	2	1	0	9	1	0	0	2	4
2	3	2	2	1	3	3	0	0	0	3	3	0
3	2	2	1	4	2	1	0	6	1	2	1	4
4	3	0	1	0	5	0	0	0	7	0	0	0
5	1	0	3	2	0	0	0	1	0	0	0	0
6	2	0	5	2	1	2	4	2	0	0	8	0

卡车数量	铲装点1	铲装点2	铲装点3	铲装点4	铲装点5	铲装点6
SA车辆数	6	6	7	4	5	7
CSA车辆数	9	6	7	5	1	7
SA-CSA车辆数	5	6	7	7	0	8

算法	总路程/km	总成本/元	总车辆数
SA	3 459.6	325 180	35
CSA	3 264.6	306 850	35
SA-CSA	3 177.8	298 680	33