基于粒子群算法的采煤工作面综机设备配套选型决策与优化研究  

Study on decision and optimization of type selection of comprehensive mechanized equipment in coal face based on particle swarm optimization

作　　者：孟祥军 阮琪 赵学强 曹凯 武越 孙飞飞 尹明虎 MENG Xiang-jun;RUAN Qi;ZHAO Xue-qiang;CAO Kai;WU Yue;SUN Fei-fei;YIN Ming-hu(Shandong Energy Group Co.,Ltd.,Jinan 250000,China;Ccdi West Testing Co.,Ltd.,Xi′an 710048,China;Yankuang Energy Group Co.,Ltd.,Jining 273500,China;Xi′an University of Technology,Xi′an 710048,China;Fangyuan Group Co.,Ltd.,Yantai 264000,China)

机构地区：[1]山东能源集团有限公司,山东济南250000 [2]中检西部检测有限公司,陕西西安710048 [3]兖矿能源集团股份有限公司,山东济宁273500 [4]西安理工大学,陕西西安710048 [5]方圆集团有限公司,山东烟台264000

出　　处：《煤炭科技》2022年第6期148-153,共6页Coal Science & Technology Magazine

摘　　要：针对由采煤工作面地质条件复杂、设备类型繁多等原因而导致的我国综机设备配套选型工作限制这一问题,将兖矿能源集团多年积累的综机设备配套经验及数据和相关综机设备配套理论、现代优化设计方法相融合,采用粒子群算法构建了以工作能力最大和成本最低为目标的工作面综机设备配套选型方案优化模型。优化前后的结果对比表明,相对于工程实际应用的配套方案,优化后方案的工作能力平均提高了16.3%、设备总价平均降低了9.6%。Aiming at the problem that the selection of comprehensive machinery equipment in China is limited due to the complex geological conditions of the coal mining face and various types of equipment, the experience and data accumulated by Yankuang Energy Group over the years in supporting comprehensive machinery equipment are combined with relevant comprehensive machinery equipment supporting theories and modern optimization design methods.The particle swarm optimization(PSO) algorithm is used to build the optimization model of the selection scheme of the comprehensive machinery equipment in the working face with the goal of maximizing the working capacity and minimizing the cost.The comparison of the results before and after the optimization shows that the working capacity of the optimized scheme is increased by 16.3% on average, and the total price of equipment is reduced by 9.6% on average, compared with the supporting scheme applied in the project.

关 键 词：综合机械化采煤 综机设备 三机配套 粒子群算法 多目标优化 

分 类 号：TH132[机械工程—机械制造及自动化]