Structural optimization using evolutionary algorithms. Nikolaos D Lagaros,Manolis Papadrakakis,George Kokossal-akis. Computers and Structures . 2002N. Lagaros, M. Papadrakakis, and G. Kokossalakis. Structural o
进化算法应用 多对象优化 Multi-Objective Optimization Using Evolutionary Algorithms 英文原版 Wiley 分享服务线下门店 · 收货后结算 选择 货源地;发货地 商品评价 暂无评价 该商品所属店铺评价 查看全部 正品(53) 质量很好(48) 物流很快(17) 坚固耐用(9) 包装很好(8) 很划算(7)...
Multi-ObjectiveOptimizationUsingEvolutionaryAlgorithms: AnIntroduction KalyanmoyDeb DepartmentofMechanicalEngineering IndianInstituteofTechnologyKanpur Kanpur,PIN208016,India deb@iitk.ac.in http://.iitk.ac.in/kangal/deb.htm February10,2011 KanGALReportNumber2011003 Abstract Asthenamesuggests,multi-objectiveoptim...
Multi-objective optimization using evolutionary algorithms
出版年:2009-3 页数:544 定价:579.00元 ISBN:9780470743614 豆瓣评分 目前无人评价 评价: 写笔记 写书评 加入购书单 分享到 内容简介· ··· The Wiley Paperback Series makes valuable content more accessible to a new generation of statisticians, mathematicians and scientists. Evolutionary algorithms are ve...
Over the last two decades, evolutionary computation (EC) has shown tremendous success for solving complex real-world problems. Although the great success for EC was first recognized in the 1980s, the researchers in other domain are still confused about the acceptability of evolutionary algorithms (...
Evolutionary techniques for multi-objective(MO) optimization are currently gainingsignificant attention from researchers invarious fields due to their effe
Therefore, this chapter will describe evolutionary algorithms that seem to respond to the characteristics required by soft computing, both with regard to versatility and to the efficiency and goodness of the results obtained. Genetic algorithms have proved to be a valid procedure for global ...
Solving Bilevel Multi-Objective Optimization Problems Using Evolutionary Algorithms 来自 ACM 喜欢 0 阅读量: 132 作者:K Deb,A Sinha 摘要: Summary: Bilevel optimization problems require every feasible upper-level solution to satisfy optimality of a lower-level optimization problem. These problems ...
Although evolutionary optimization algorithms can be used in this way, more often they’re used to find the values for a set of numeric parameters in a larger optimization problem for which there’s no effective deterministic algorithm. For example, when using a neural network to classify ...