一种自适应差分进化算法在煤气分配中的应用
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摘要
通过分析钢铁生产过程中主要能耗设备的煤气使用特征及煤气分配过程中的约束,建立了以煤气消耗成本、放散成本及发电收益之和最小化的数学模型,提出了一种自适应混合差分进化算法(AHDE)进行求解。算法利用蚁群算法在路径选择能力方面的优势,构造算法中差分策略选择机制提高算法的性能。通过对标准测试函数和对实际生产数据的仿真实验,验证算法的有效性。
By analyzing the gas using characteristics and constrains of the main energy consumption equipment in the process of gas distribution for iron and steel production,a mathematical model for gas distribution was formulated whose objective was to minimize the sum including consumption cost,emission cost and benefit from electric power generation.An adaptive hybrid differential evolution algorithm(AHDE)was proposed to solve the model which took advantage of the superiority ability in the aspect of path selection of ant colony optimization algorithm,and designed the selection mechanism of differential strategy,and improved the algorithm performance.The effectiveness of the proposed algorithm was verified by the simulation test based on the practical production data with the standard test functions.
By analyzing the gas using characteristics and constrains of the main energy consumption equipment in the process of gas distribution for iron and steel production,a mathematical model for gas distribution was formulated whose objective was to minimize the sum including consumption cost,emission cost and benefit from electric power generation.An adaptive hybrid differential evolution algorithm(AHDE)was proposed to solve the model which took advantage of the superiority ability in the aspect of path selection of ant colony optimization algorithm,and designed the selection mechanism of differential strategy,and improved the algorithm performance.The effectiveness of the proposed algorithm was verified by the simulation test based on the practical production data with the standard test functions.
引文
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[2]张小雷,张颜颜,唐立新.钢铁企业煤气混合优化分配模型[J].系统工程学报,2011,26(5):710.
[3]齐二石,孔海宁,何曙光.钢铁企业副产煤气多周期动态优化调度[J].系统工程理论与实践,2010,30(11):2071.
[4]李红娟,王建军,王华,等.基于HP(2)-Elman模型的钢铁企业富余煤气预测及优化调度[J].钢铁研究学报,2013,25(7):11.
[5]Yang J,Cai J,Sun W,et al.Optimization and scheduling of byproduct gas system in steel plant[J].Journal of Iron and Steel Research,International,2015,22(5):408.
[6]Zhang X,Zhao J,Wang W,et al.An optimal method for prediction and adjustment on byproduct gas holder in steel industry[J].Expert Systems with Applications,2011,38(4):4588.
[7]李智,苏福永,温治,等.遗传算法的改进及在钢铁企业煤气调度中的应用[J].东北大学学报:自然科学版,2014,35(5):645.
[8]Lin S,Luan F,Han Z,et al.Genetic algorithm based on duality principle for bilevel programming problem in steel-making production[J].Chinese Journal of Chemical Engineering,2014,22(7):742.
[9]Storn R,Price K.Differential evolution-A simple and efficient heuristic for global optimization over continuous spaces[J].Journal of Global Optimization,1997,11(4):341.
[10]Storn R,Price K.Differential evolution—a simple and efficient adaptive scheme for global optimization over continuous spaces[R].Berkeley:ICSI,1995.
[11]Kim H K,Chong J K,Park K Y.Differential evolution strategy for constrained global optimization and application to practical engineering problems[J].IEEE Transactions on Magnetics,2007,43(4):1565.
[12]Dhahri H,Alimi A M.The modified differential evolution and the RBF(MDE-RBF)neural network for time series prediction[C]//Proceeds of the International Joint Conference on Neural Networks.Vancouver:IEEE,2006.
[13]Dorigo M,Maniezzo V,Colorni A.Ant system:optimization by a colony of cooperating agents[J].IEEE Transactions on Systems,Man and Cybernetics,1996,26B(1):29.
[14]Dorigo M,Di Caro G.Ant colony optimization:a new metaheuristic[C]//The Congress on Evolutionary Computation.Washington,DC:IEEE,1999.
[15]贺毅朝,王熙照,刘坤起,等.差分演化的收敛性分析与算法改进[J].软件学报,2010,21(5):875.