基于PGA-ANFIS的露天矿山开采调度系统的实时优化与实践
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摘要
矿山开采调度系统主要解决不同平台开采的穿孔爆破技术经济参数优化问题。本文以雪峰水泥原料矿山为例,运用自适应模糊推理系统方法构造露天矿山开采调度系统模型,用并行遗传算法解决了不确定环境条件下的复杂矿山开采调度系统模型的优化问题,取得了较好的经济效益。这不仅为生产调度系统的在线优化问题提供了新的思路,而且为穿孔爆破参数的优化提供了新的方法,对促进矿山生产系统的自动化、信息化、智能化、集约化具有重要的参考价值。
Mining Scheduling System model is mainly used for the optimization of drilling-blasting technical and economic parameters of different platforms.By taking Xuefeng cement material quarry as an example,this paper constructed strip Mining Scheduling System model with Adaptive Network-based Fuzzy Inference System,and solved optimization problem of complicated quarry Mining Scheduling System under uncertainty by Parallel Genetic Algorithms.The application of this system brought good economic benefit.The research not only provides new idea for on-line optimization problem of Mining Scheduling System,but also provides theory for optimizing drilling-blasting parameter,and furthermore,provides important reference to the automatization,informazation,intelligentization and intergration of quarry production system.
Mining Scheduling System model is mainly used for the optimization of drilling-blasting technical and economic parameters of different platforms.By taking Xuefeng cement material quarry as an example,this paper constructed strip Mining Scheduling System model with Adaptive Network-based Fuzzy Inference System,and solved optimization problem of complicated quarry Mining Scheduling System under uncertainty by Parallel Genetic Algorithms.The application of this system brought good economic benefit.The research not only provides new idea for on-line optimization problem of Mining Scheduling System,but also provides theory for optimizing drilling-blasting parameter,and furthermore,provides important reference to the automatization,informazation,intelligentization and intergration of quarry production system.
引文
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(7)Pohlheim H,Pawletta S,Westphal A.Parallel EvolutionaryOptimization under Matlab on Standard Computing Net-works[C].In:[CEC99],Evolutionary Computation andParallel Processing Workshop,1999,174-176.http://www.pohlheim.com/papers pohlheim.html.
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(12)Fonseca C M.Multiobjective Genetic Algorithms with Ap-plication to Control Engineering Problems[D].Thesis,De-partment of Automatic Control and Systems Engineering,U-niversity of Sheffield,Sheffield,U K,1995.
(2)郭嗣琮,陈刚.信息科学中的软计算方法[M].沈阳:东北大学出版社,2001.
(3)Haas R,Hunt K J.Genetic Based Optimisation of a Fuzzy-Neural Vehicle Controller[R].Technical Report,DaimlerBenz AG,Research and Technology,Berlin,1994.
(4)飞思科技产品研发中心.MATLAB6.5辅助优化计算与设计[M].北京:电子工业出版社,2003.1(MATLAB应用技术).
(5)Chipperfield A,Fleming P,Pohlheim H,Fonseca C.GeneticAlgorithm TOOLBOX for Use with MATLAB Version1.2User’s Guide[M].
(6)Michalewicz Z.Genetic Algorithms+Data Structures=Evo-lution Programs,Second,Extended Edition[M].Berlin,Hei-delberg,New York:Springer-Verlag,1994.
(7)Pohlheim H,Pawletta S,Westphal A.Parallel EvolutionaryOptimization under Matlab on Standard Computing Net-works[C].In:[CEC99],Evolutionary Computation andParallel Processing Workshop,1999,174-176.http://www.pohlheim.com/papers pohlheim.html.
(8)王小平,曹立明.遗传算法———理论、应用与软件实现[M].西安:西安交通大学出版社,2002.
(9)Li Y,Ng K C.Uniform Approach to Model-based FuzzyControl System Design and Structural Optimization[C].In:Genetic Algorithms and Soft Computing,Herrera F andVerdegay J(ed),Physica Verlag,1996,129-151.
(10)欧进萍,张利芬.模糊神经网络控制系统优化的实整数混合编码遗传算法[J].地震工程与工程振动,2003,23(1):11-17.
(11)Fonseca C M,Fleming P J.Multiobjective Optimizationand Multiple Constraint Handling with Evolutionary Algo-rithms I:A Unified Formulation[M].Research Report 564,Dept.Automatic Control and Systems Eng.,University ofSheffield;Sheffield,U.K.,1995.
(12)Fonseca C M.Multiobjective Genetic Algorithms with Ap-plication to Control Engineering Problems[D].Thesis,De-partment of Automatic Control and Systems Engineering,U-niversity of Sheffield,Sheffield,U K,1995.
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