工程科学学报，第40卷，第9期：1050-1057,2018年9月 Chinese Journal of Engineering,Vol.40,No.9:1050-1057,September 2018 DOI:10.13374/j.issn2095-9389.2018.09.005;http://journals.ustb.edu.cn 地下矿山生产接续与设备调度集成优化模型 李国清12，侯杰12)，胡乃联2) 1)北京科技大学土木与资源工程学院，北京1000832)金属矿山高效开采与安全教有部重点实验室，北京100083 ☒通信作者，E-mail:ustbhoujie(@hotmail.com 摘要为了实现地下金属矿山生产接续的紧凑性、科学高效地调度生产设备，针对矿山开采工序复杂、设备资源有限、生产 任务量大等特点，以最短工序时间间隔和最短总完成时间为共同优化目标构建了地下矿山生产接续与设备调度集成优化模 型.通过分析地下矿山生产循环顺序、作业设备类型和生产能力等生产要素，考虑工序闲置期间采场的安全隐患问题，运用改 进遗传算法对最优解进行主一从两步骤搜索，得到地下矿山生产接续和设备调度最佳方案.以国内某大型金矿为案例进行了 模型的有效性验证，解算出矿山最优的设备调度计划.验证结果表明，与传统的单一目标优化相比，模型在保证完成指定任务 的同时，有效缩短工序时间间隔，并且保证了作业的安全要求. 关键词地下金属山：集成优化：生产接续：设备调度：改进遗传算法 分类号TG142.71 Integrated optimization model for production and equipment dispatching in underground mines LI Guo-qing2),HOU Jie HU Nai-ian) 1)School of Civil and Resource Engineering,University of Science and Technology Beijing,Beijing 100083,China 2)Key Laboratory of High-Efficient Mining and Safety of Metal Mines,Ministry of Education,Beijing 100083,China Corresponding author,E-mail:ustbhoujie@hotmail.com ABSTRACT Integrated optimization of production plays a key role in realizing short completion times of underground mine processes. To achieve the best production operation,a production plan should consider factors such as the working time and equipment capacity to arrange stope mining operations,equipment,and materials supply.Underground mining operation is a process with multiple working sites and multiple cycle operations,which include rock drilling,blasting,ventilation,supporting,ore-transportation,and backfilling. Once the stope mining begins,the above six steps must be intensively integrated to minimize the exposure time.Each step of stope min- ing has a significant effect on the whole mining plan;therefore,it is very important to form a reasonable configuration to achieve the mining plan target.The most difficult part of underground mining operation is how to organize the production process with limited re- sources (i.e.,equipment and materials)to accomplish a large production task.In this paper,an integrated optimization model was described for compacting the integrated production process and efficiently dispatching production equipment.Two optimal objectives were combined to shorten the interval between production processes and overall working time.Production factors such as production cy- cle,type of operation equipment,and production capacity are analyzed in a mathematical model.In addition,the production safety was also considered and the time intervals between different working processes were considered to shorten the stope uncontrolled time to keep the production safety in the mathematical model.The best result of mining sequence and equipment dispatching was obtained by an improved genetic algorithm which searches the feasible solutions through primary-secondary two-step searching method.The model was validated in a large gold mine in China to work out the optimal equipment scheduling plan.The results show that compared with the 收稿日期：201804-16 基金项目：国家自然科学基金资助项目(71573012)工程科学学报，第 40 卷，第 9 期: 1050--1057，2018 年 9 月 Chinese Journal of Engineering，Vol． 40，No． 9: 1050--1057，September 2018 DOI: 10． 13374 /j． issn2095--9389． 2018． 09． 005; http: / /journals． ustb． edu． cn 地下矿山生产接续与设备调度集成优化模型 李国清1，2) ，侯 杰1，2) ，胡乃联1，2) 1) 北京科技大学土木与资源工程学院，北京 100083 2) 金属矿山高效开采与安全教育部重点实验室，北京 100083 通信作者，E-mail: ustbhoujie@ hotmail． com 摘 要 为了实现地下金属矿山生产接续的紧凑性、科学高效地调度生产设备，针对矿山开采工序复杂、设备资源有限、生产 任务量大等特点，以最短工序时间间隔和最短总完成时间为共同优化目标构建了地下矿山生产接续与设备调度集成优化模 型． 通过分析地下矿山生产循环顺序、作业设备类型和生产能力等生产要素，考虑工序闲置期间采场的安全隐患问题，运用改 进遗传算法对最优解进行主--从两步骤搜索，得到地下矿山生产接续和设备调度最佳方案． 以国内某大型金矿为案例进行了 模型的有效性验证，解算出矿山最优的设备调度计划． 验证结果表明，与传统的单一目标优化相比，模型在保证完成指定任务 的同时，有效缩短工序时间间隔，并且保证了作业的安全要求． 关键词 地下金属矿山; 集成优化; 生产接续; 设备调度; 改进遗传算法 分类号 TG142. 71 收稿日期: 2018--04--16 基金项目: 国家自然科学基金资助项目( 71573012) Integrated optimization model for production and equipment dispatching in underground mines LI Guo-qing1，2) ，HOU Jie1，2)  ，HU Nai-lian1，2) 1) School of Civil and Ｒesource Engineering，University of Science and Technology Beijing，Beijing 100083，China 2) Key Laboratory of High-Efficient Mining and Safety of Metal Mines，Ministry of Education，Beijing 100083，China Corresponding author，E-mail: ustbhoujie@ hotmail． com ABSTＲACT Integrated optimization of production plays a key role in realizing short completion times of underground mine processes． To achieve the best production operation，a production plan should consider factors such as the working time and equipment capacity to arrange stope mining operations，equipment，and materials supply． Underground mining operation is a process with multiple working sites and multiple cycle operations，which include rock drilling，blasting，ventilation，supporting，ore-transportation，and backfilling． Once the stope mining begins，the above six steps must be intensively integrated to minimize the exposure time． Each step of stope min￾ing has a significant effect on the whole mining plan; therefore，it is very important to form a reasonable configuration to achieve the mining plan target． The most difficult part of underground mining operation is how to organize the production process with limited re￾sources ( i． e． ，equipment and materials) to accomplish a large production task． In this paper，an integrated optimization model was described for compacting the integrated production process and efficiently dispatching production equipment． Two optimal objectives were combined to shorten the interval between production processes and overall working time． Production factors such as production cy￾cle，type of operation equipment，and production capacity are analyzed in a mathematical model． In addition，the production safety was also considered and the time intervals between different working processes were considered to shorten the stope uncontrolled time to keep the production safety in the mathematical model． The best result of mining sequence and equipment dispatching was obtained by an improved genetic algorithm which searches the feasible solutions through primary-secondary two-step searching method． The model was validated in a large gold mine in China to work out the optimal equipment scheduling plan． The results show that compared with the