[1]孟勤超,杨翠丽,乔俊飞.基于改进SPEA2算法的给水管网多目标优化设计[J].智能系统学报,2018,13(1):118-124.[doi:10.11992/tis.201701012]
 MENG Qinchao,YANG Cuili,QIAO Junfei.Multi-objective optimization design of water distribution systems based on improved SPEA2 algorithm[J].CAAI Transactions on Intelligent Systems,2018,13(1):118-124.[doi:10.11992/tis.201701012]
点击复制

基于改进SPEA2算法的给水管网多目标优化设计

参考文献/References:
[1] ALPEROVITS E, SHAMIR U. Design of optimal water distribution systems[J]. Water resources research, 1977, 13(6): 885-900.
[2] 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.
[3] MORGAN D R, GOULTER I C. Optimal urban water distribution design[J]. Water resources research, 1985, 21(5): 642-652.
[4] HALHAL D, WALTERS G A, OUAZAR D, et al. Water network rehabilitation with structured messy genetic algorithm[J]. Journal of water resources planning and management, 1997, 123(3): 137-146.
[5] MONTALVO I, IZQUIERDO J, SCHWARZE S, et al. Multi-objective particle swarm optimization applied to water distribution systems design: an approach with human interaction[J]. Mathematical and computer modelling, 2010, 52(7/8): 1219-1227.
[6] LIU Haixing, YUAN Yixing, ZHAO Ming, et al. Hybrid multi-objective genetic algorithm for optimal design of water supply network[C]//Proceedings of the 12th Annual Conference on Water Distribution Systems Analysis. Tucson, United States, 2010: 899-908.
[7] 刘书明, 李明明, 王欢欢, 等. 基于NSGA-Ⅱ算法的给水管网多目标优化设计[J]. 中国给水排水, 2015, 31(5): 50-53.
LIU Shuming, LI Mingming, WANG Huanhuan, et al. Multi-objective optimization design of water distribution system based on non-dominated sorting genetic algorithm-Ⅱ[J]. China water & wastewater, 2015, 31(5): 50-53.
[8] 蒋怀德. 给水管网多目标优化设计[D]. 上海:同济大学, 2007, 5–7.
JIANG Huaide. Multi-objective optimization design of urban water distribution networks[D]. Shanghai: Tongji University, 2007, 5–7.
[9] LI Mingming, LIU Shuming, ZHANG Ling, et al. Non-dominated sorting genetic algorithms-iibased on multi-objective optimization model in the water distribution system[J]. Procedia engineering, 2012, 37: 309-313.
[10] TOLSON B A, MAIER H R, SIMPSON A R, et al. Genetic algorithms for reliability-based optimization of water distribution systems[J]. Journal of water resources planning and management, 2004, 130(1): 63-72.
[11] ZITZLER E, LAUMANNS M, THIELE L. SPEA2: improving the strength Pareto evolutionary algorithm: TIK-Report 103[R]. Swiss: Swiss Federal Institute of Technology, 2001.
[12] DEB K, PRATAP A, AGARWAL S, et al. A fast and elitist multiobjective genetic algorithm: NSGA-Ⅱ[J]. IEEE transactions on evolutionary computation, 2002, 6(2): 182-197.
[13] ZHANG Qingfu, LI Hui. MOEA/D: a multiobjective evolutionary algorithm based on decomposition[J]. IEEE transactions on evolutionary computation, 2007, 11(6): 712-731.
[14] DEB K, JAIN H. An evolutionary many-objective optimization algorithm using reference-point-based nondominated sorting approach, part I: solving problems with box constraints[J]. IEEE transactions on evolutionary computation, 2014, 18(4): 577-601.
[15] PRASAD T D, PARK N S. Multiobjective genetic algorithms for design of water distribution networks[J]. Journal of water resources planning and management, 2004, 130(1): 73-82.
[16] JIANG Siwei, CAI Zhihua, ZHANG Jie, et al. Multiobjective optimization by decomposition with Pareto-adaptive weight vectors[C]//International Conference on Natural Computation, Icnc 2011, Shanghai, China, 26-28 July. DBLP, 2011: 1260-1264.
[17] 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.
[18] MA Xiaoliang, LIU Fang, QI Yutao, et al. A multiobjective evolutionary algorithm based on decision variable analyses for multiobjective optimization problems with large-scale variables[J]. IEEE transactions on evolutionary computation, 2016, 20(2): 275-298.
[19] TANG Lixin, WANG Xianpeng. A hybrid multiobjective evolutionary algorithm for multiobjective optimization problems[J]. IEEE transactions on evolutionary computation, 2013, 17(1): 20-45.
[20] JIANG Shouyong, YANG Shengxing. Evolutionary dynamic multiobjective optimization: benchmarks and algorithm comparisons[J]. IEEE transactions on cybernetics, 2017, 47(1): 198-211.
相似文献/References:
[1]王 艳,曾建潮.多目标微粒群优化算法综述[J].智能系统学报,2010,5(5):377.[doi:10.3969/j.issn.1673-4785.2010.05.001]
 WANG Yan,ZENG Jian-chao.A survey of a multiobjective particle swarm optimization algorithm[J].CAAI Transactions on Intelligent Systems,2010,5():377.[doi:10.3969/j.issn.1673-4785.2010.05.001]
[2]陶新民,徐鹏,刘福荣,等.组合分布估计和差分进化的多目标优化算法[J].智能系统学报,2013,8(1):39.[doi:10.3969/j.issn.1673-4785.201208035]
 TAO Xinmin,XU Peng,LIU Furong,et al.Multi objective optimization algorithm composed of estimation of distribution and differential evolution[J].CAAI Transactions on Intelligent Systems,2013,8():39.[doi:10.3969/j.issn.1673-4785.201208035]
[3]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,2015,10(5):722.[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():722.[doi:10.11992/tis.201410036]
[4]秦全德,程适,李丽,等.人工蜂群算法研究综述[J].智能系统学报,2014,9(2):127.[doi:10.3969/j.issn.1673-4785.201309064]
 QIN Quande,CHENG Shi,LI Li,et al.Artificial bee colony algorithm: a survey[J].CAAI Transactions on Intelligent Systems,2014,9():127.[doi:10.3969/j.issn.1673-4785.201309064]
[5]张伟,乔俊飞.神经网络的污水处理过程多目标优化控制方法[J].智能系统学报,2016,11(5):594.[doi:10.11992/tis.201512022]
 ZHANG Wei,QIAO Junfei.Multi-objective optimization control for wastewatertreatment processing based on neural network[J].CAAI Transactions on Intelligent Systems,2016,11():594.[doi:10.11992/tis.201512022]
[6]屠传运,陈韬伟,余益民,等.膜系统下的一种多目标优化算法[J].智能系统学报,2017,12(5):678.[doi:10.11992/tis.201706013]
 TU Chuanyun,CHEN Taowei,YU Yimin,et al.Multi-objective optimization algorithm based on membrane system[J].CAAI Transactions on Intelligent Systems,2017,12():678.[doi:10.11992/tis.201706013]
[7]林燕清,傅仰耿.基于NSGA-II的扩展置信规则库激活规则多目标优化方法[J].智能系统学报,2018,13(3):422.[doi:10.11992/tis.201710012]
 LIN Yanqing,FU Yanggeng.NSGA-II-based EBRB rules activation multi-objective optimization[J].CAAI Transactions on Intelligent Systems,2018,13():422.[doi:10.11992/tis.201710012]
[8]柳强,焦国帅.基于Kriging模型和NSGA-Ⅱ的航空发动机管路卡箍布局优化[J].智能系统学报,2019,14(2):281.[doi:10.11992/tis.201709044]
 LIU Qiang,JIAO Guoshuai.Layout optimization of aero-engine pipe clamps based on Kriging model and NSGA-Ⅱ[J].CAAI Transactions on Intelligent Systems,2019,14():281.[doi:10.11992/tis.201709044]
[9]钱小宇,葛洪伟,蔡明.基于目标空间分解和连续变异的多目标粒子群算法[J].智能系统学报,2019,14(3):464.[doi:10.11992/tis.201711015]
 QIAN Xiaoyu,GE Hongwei,CAI Ming.Decomposition and continuous mutation-based multi-objective particle swarm optimization[J].CAAI Transactions on Intelligent Systems,2019,14():464.[doi:10.11992/tis.201711015]
[10]林锦,胡家琛,刘莞玲,等.利用MISA多目标优化的置信规则库分类算法[J].智能系统学报,2019,14(5):982.[doi:10.11992/tis.201809022]
 LIN Jin,HU Jiachen,LIU Wanling,et al.Belief rule base classification algorithm using MISA multi-objective optimization[J].CAAI Transactions on Intelligent Systems,2019,14():982.[doi:10.11992/tis.201809022]

备注/Memo

收稿日期:2017-01-15。
基金项目:国家自然科学基金项目(61533002, 61603012).
作者简介:孟勤超,男,1993年生,硕士研究生,主要研究方向为智能优化算法及其应用;杨翠丽,女,1986年生,讲师,博士研究生,主要研究方向为进化算法和智能信息处理。发表学术论文10余篇,其中SCI检索7篇,EI检索12篇;乔俊飞,男,1968年生,教授,博士生导师,主要研究方向为智能信息处理、智能优化控制。近5年在Automatica、IEEE Transactionson Control Systems Technology、Journal of Process Control、Control Engineering Practice、自动化学报及电子学报等刊物上发表学术论文近70篇,被SCI收录15篇。获教育部科技进步奖一等奖和北京市科学技术奖三等奖各1项,获得授权国家发明专利12项。
通讯作者:孟勤超.E-mail:qinchaomeng@foxmail.com.

更新日期/Last Update: 2018-02-01
Copyright @ 《 智能系统学报》 编辑部
地址:(150001)黑龙江省哈尔滨市南岗区南通大街145-1号楼 电话:0451- 82534001、82518134