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作 者:顾清华[1] 王雪晴 王丹[2] 张朋朋 王宇 GU Qinghua;WANG Xueqing;WANG Dan;ZHANG Pengpeng;WANG Yu(School of Resources Engineering,Xi’an University of Architecture and Technology,Xi’an Shaanxi 710055,China;School of Management,Xi’an University of Architecture and Technology,Xi’an Shaanxi 710055,China;PowerChina Roadbridge Group Co.,Ltd.,Beijing 100160,China;Northwest Engineering Co.,Ltd.,Xi’an Shaanxi 710065,China)
机构地区:[1]西安建筑科技大学资源工程学院,陕西西安710055 [2]西安建筑科技大学管理学院,陕西西安710055 [3]中电建路桥集团有限公司,北京100160 [4]中国电建集团西北勘测设计研究院有限公司,陕西西安710065
出 处:《矿业科学学报》2025年第2期305-315,共11页Journal of Mining Science and Technology
基 金:国家自然科学基金(52374135,52074205);陕西省金属矿智能开采理论及技术创新团队(2023-CX-TD-12)。
摘 要:为减少露天矿开采设备突发故障的不确定性和随机性影响,以露天煤矿运输系统中的装载点和卸载点的生产设备为研究对象,提出考虑设备突发故障的露天矿无人矿卡集群调度模型。首先,以最小化卡车运输成本、卡车总空闲时间以及最大化矿石运量为目标,建立初始调度模型;其次,考虑设备突发故障,构建与初始调度方案目标函数偏差最小的重新调度模型,进而提出一种基于代理模型辅助的自适应选择多目标进化算法,用克里金(Kriging)代理模型代替卡车调度仿真过程;最后,以国内某露天矿的相关数据进行仿真应用。结果表明:当运输系统受到设备突发故障干扰时,该方法能给出卡车总空闲时间更短以及矿石运量更多的调度优化调整方案。To reduce the impact of uncertainty and randomness of sudden equipment failures in open-pit mining equipment,taking the production equipment at the loading and unloading points in the transportation system of open-pit coal mines as the research object,an unmanned mining truck cluster scheduling model for open-pit mines considering sudden equipment failures is proposed.Firstly,an initial scheduling model is established to minimize truck transportation costs,total idle time of trucks,and maximize ore transportation volume.Secondly,considering sudden equipment failures,a rescheduling model is constructed to minimize the deviation from the objective function of the initial scheduling plan.Subsequently,an adaptive multi-objective evolutionary algorithm assisted by a surrogate model is proposed,using Kriging surrogate models to replace the truck dispatching simulation process.Finally,the method is applied to simulation with data from a domestic open-pit mine. The results show that when the transportation system is disturbed by sudden equipment failures, this method can provide a schedu-ling optimization adjustment plan with shorter total idle time of trucks and more ore transportation volume.
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