[1]王超,乔俊飞.参数自适应粒子群算法的给水管网优化研究[J].智能系统学报编辑部,2015,10(5):722-728.[doi:10.11992/tis.201410036]
 WANG Chao,QIAO Junfei.An parameter adaptive particle swarm optimization foroptimal design of water supply systems[J].CAAI Transactions on Intelligent Systems,2015,10(5):722-728.[doi:10.11992/tis.201410036]
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参数自适应粒子群算法的给水管网优化研究

参考文献/References:
[1] MURPHY L J, SIMPSON A R, Dandy G C. Design of a pipe network using genetic algorithms[J]. Water-Melbourne Then Artarmon, 1993, 20(4):40-42.
[2] ABKENAR S M S, CHASE D V, STANLEY S D, et al. Optimizing pumping system for sustainable water distribution network by using genetic algorithm[C]//2013 International Green Computing Conference. Arlington, USA, 2013:1-6.
[3] BLINCO L J, SIMPSON A R, LAMBERT M F, et al. Genetic algorithm optimization of operational costs and greenhouse gas emissions for water distribution systems[J]. Procedia Engineering, 2014, 89:509-516.
[4] DINARDO A, DINATALE M, GRECO R, et al. Ant algorithm for smart water network partitioning[J]. Procedia Engineering, 2014, 70:525-534.
[5] MOOSAVIAN N, ROODSARI B K. Soccer league competition algorithm:a novel meta-heuristic algorithm for optimal design of water distribution networks[J]. Swarm and Evolutionary Computation, 2014, 17:14-24.
[6] LIU Boning, RECKHOW D A, LI Yun. A two-site chlorine decay model for the combined effects of pH, water distribution temperature and in-home heating profilesusing differential evolution[J]. Water Research, 2014, 53:47-57.
[7] NASER M, ROODSARIB K. Soccer league competition algorithm:A novel meta-heuristic algorithm for optimal design of water distribution networks[J]. Swarm and Evolutionary Computation, 2014, 17:14-24.
[8] WANG Hongxiang, GUO Wenxian. Calibrating chlorine wall decay coefficients of water distribution systems based on hybrid PSO[C]//Sixth International Conference on Natural Computation (ICNC). Yantai, China, 2010:3856-3860.
[9] MONTALVO I M, IZQUIERDO J, PÉREZ R, et al. A diversity-enriched variant of discrete PSO applied to the design of water distribution networks[J]. Engineering Optimization, 2008, 40(7):655-668.
[10] ZARGHAMIM, HAJYKAZEMIAN H. Urban water resources planning by using a modified particle swarm optimization algorithm[J]. Resources, Conservation and Recycling, 2013, 70:1-8.
[11] HASHEMI A B, MEYBODI M R. A note on the learning automata based algorithms for adaptive parameter selection in PSO[J]. Applied Soft Computing, 2011, 11(1):689-705.
[12] DE FÁTIMA ARAU’JO T, UTURBEY W. Performance assessment of PSO, DE and hybrid PSO-DE algorithms when applied to the dispatch of generation and demand[J]. International Journal of Electrical Power & Energy Systems, 2013, 47:205-217.
[13] 刘建华, 樊晓平, 瞿志华. 一种基于相似度的新型粒子群算法[J]. 控制与决策, 2007, 22(10):1155-1159.LIU Jianhua, FAN Xiaoping, QU Zhihua. A new particle swarm optimization algorithm based on similarity[J]. Control and Decision, 2007, 22(10):1155-1159.
[14] COELHO B, ANDRADE-CAMPOS A. Efficiency achievement in water supply systems-a review[J]. Renewable and Sustainable Energy Reviews, 2014, 30:59-84.
[15] ANNELIES D C, KENNETH S. Optimisation of gravity-fed water distribution network design:a critical review[J]. European Journal of Operational Research, 2013, 228(1):1-10.
[16] 李宁, 孙德宝, 邹彤, 等. 基于差分方程的PSO算法粒子运动轨迹分析[J]. 计算机学报, 2006, 29(11):2052-2061.LI Ning, SUN Debao, ZOU Tong, et al. An analysis for a particle’s trajectory of PSO based on difference equation[J]. Chinese Journal of Computers, 2006, 29(11):2052-2061.
[17] VANDEN BERGH F. An analysis of particle swarm optimizers[D]. Pretoria, South Africa:University of Pretoria, 2002:81-83.
[18] SEDKI A, OUAZAR D. Hybrid particle swarm optimization and differential evolution for optimal design of water distribution systems[J]. Advanced Engineering Informatics, 2012, 26(3):582-591.
[19] SAVIC D A, WALTERS G A. Genetic algorithms for least cost design of water distribution networks[J]. Journal of Water Resources Planning and Management, 1997, 123(2):67-77.
[20] IDEL M, JOAQUIN I, RAFAEL P G, et al. Improved performance of PSO with self-adaptive parameters for computing the optimal design of water supply systems[J]. Engineering Applications of Artificial Intelligence, 2010, 23(5):727-735.
[21] SURIBABU C R. Differential evolution algorithm for optimal design of water distribution networks[J]. Journal of Hydroinformatics, 2010, 12(1):66-82.
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备注/Memo

收稿日期:2014-10-27;改回日期:。
基金项目:国家自然科学基金重点资助项目(61034008);国家自然科学基金杰出青年资助项目(61225016);北京市自然科学基金资助项目(4122006).
作者简介:王超,男,1987年生,硕士研究生,主要研究方向为智能计算和智能优化算法;乔俊飞,男,1968年生,教授,博士,主要研究方向为复杂过程建模、优化与控制和智能优化控制。主持国家自然科学基金项目2项、国家“863”计划项目2项,发表学术论文100余篇,出版专著2部,获国家发明专利授权15项。
通讯作者:乔俊飞.E-mail:isibox@sina.com.

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