杨建军1,21 1,丁玉成,赵万华.基于双重编码遗传算法和图论的自压树状管网优化[J].农业机械学报,2010,41(1):. Yang Jianjun,Ding Yucheng,Zhao Wanhua.Optimization of Gravity Tree type Pipe Network Based on Dual Coding Genetic Algorithm and Graph Theory[J].Transactions of the Chinese Society for Agricultural Machinery,2010,41(1):.
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摘要点击次数: 3087 全文下载次数: 1672
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基于双重编码遗传算法和图论的自压树状管网优化 [下载全文] |
Optimization of Gravity Tree type Pipe Network Based on Dual Coding Genetic Algorithm and Graph Theory [Download Pdf][in English] |
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DOI:10.3969/j.issn.1000-1298.2010.1.016 |
中文关键词: 树状管网 优化 遗传算法 双重编码 图论 |
基金项目:国家“863”高技术研究发展计划资助项目(2006AA100208)和泰山学者建设工程
专项
经费资助项目(2007) |
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中文摘要:以投资最小为目标函数,压力、流速、管径等限制为约束条件,建立了自压树状管网优化数
学模型,并采用改进遗传算法进行求解。根据树状管网优化的特点,遗传算法采用二进制编
码和整数编码相结合的双重编码,实现了同时对管网布置形式和管径进行优化。根据图论中
树的性质,在产生初始解及变异操作时,采用基于圈的方法,对交叉方法进行了改进,从
而减少了不可行解的产生。同时对遗传算法的操作过程进行了改进,结合了模拟退火算法,
调整了适应函数,改进了交叉率和变异率的计算方法。算例表明了该优化方法的有效性。 |
Yang Jianjun Ding Yucheng Zhao Wanhua |
State Key Laboratory for Manufacturing Systems Engineering, Xi’an Jiaotong
University, Xi’an 710049, China
;School of Mechanical Engineering, Qingdao Technological University,Qingdao 2
66033, China;chool of Mechanical Engineering, Qingdao Technological University,Qingdao 2
66033, China;chool of Mechanical Engineering, Qingdao Technological University,Qingdao 2
66033, China |
Key Words:Tree type pipe network, Optimization, Genetic algorithm, Dual coding, Graph the
ory |
Abstract:An optimization model for gravity tree type pipe network is established, in whi
ch the minimal investment is taken as the objective function, and the pressu
re, flow rate and pipe diameter are taken as the constraint conditions. The impr
oved genetic algorithm is used to solve the problem. Based on the optimal featur
es of tree type pipe network, the dual coding combining binary coding with inte
ger coding is adopted in the genetic algorithm to optimize the pipe layout and p
ipe diameter simultaneously. Based on characteristics of tree in the graph theor
y, the cycle method is adopted to improve cross method in the operations of init
ial solution creating and mutation so that the number of infeasible solutions is
reduced. Some operational processes of genetic algorithm are improved. The simu
lated annealing algorithm is introduced in the model. The fitness function is ad
justed, and the computing methods of crossover rate and mutation rate are improv
ed. Example shows that the algorithm is efficient. |
Transactions of the Chinese Society for Agriculture Machinery (CSAM), in charged of China Association for Science and Technology (CAST), sponsored by CSAM and Chinese Academy of Agricultural Mechanization Science(CAAMS), started publication in 1957. It is the earliest interdisciplinary journal in Chinese which combines agricultural and engineering. It always closely grasps the development direction of agriculture engineering disciplines and the published papers represent the highest academic level of agriculture engineering in China. Currently, nearly 8,000 papers have been already published. There are around 3,000 papers contributed to the journal each year, but only around 600 of them will be accepted. Transactions of CSAM focuses on a wide range of agricultural machinery, irrigation, electronics, robotics, agro-products engineering, biological energy, agricultural structures and environment and more. Subjects in Transactions of the CSAM have been embodied by many internationally well-known index systems, such as: EI Compendex, CA, CSA, etc.
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