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1.An improved multi-objective evolutionary algorithm based on environmental and history information

作者：Ziyu Hu^a ; ^b ; ^{whoziyu@163.com}Author Vitae ; Jingming Yang^a ; ^bAuthor Vitae ; Hao Sun^a ; ^bAuthor Vitae ; Lixin Wei^a ; ^bAuthor Vitae ; Zhiwei Zhao^a ; ^cAuthor Vitae

关键词：Evolutionary computation ; Multi-objective optimization ; Exploitation and exploration ; Evolutionary algorithm

刊名：Neurocomputing

出版年：2017

2.Quantum inspired evolutionary algorithm for ordering problems

作者：Luciano Reis da Silveira ^{lucianoreisdasilveira@gmail.com" class="auth_mail" title="E-mail the corresponding author} ; Ricardo Tanscheit ^{ricardo@ele.puc-rio.br" class="auth_mail" title="E-mail the corresponding author} ; Marley M.B.R. Vellasco ; ^{marley@ele.puc-rio.br" class="auth_mail" title="E-mail the corresponding author}

关键词：Quantum inspired evolutionary algorithm ; Ordering optimization problem ; Quantum bit ; Vehicle routing problem

刊名：Expert Systems with Applications

出版年：2017

3.Sampling-based adaptive bounding evolutionary algorithm for continuous optimization problems

作者：Linbo Luo ; ^a ; ^{lbluo@xidian.edu.cn} ; Xiangting Hou^b ; Jinghui Zhong^c ; Wentong Cai^b ; Jianfeng Ma^a

关键词：Search space narrowing ; Adaptive bounding evolutionary algorithm ; Continuous optimization problem ; Simulation model calibration

刊名：Information Sciences

出版年：2017

4.A proper infill sampling strategy for improving the speed performance of a Surrogate-Assisted Evolutionary Algorithm

作者：Loris Vincenzi ; ^{loris.vincenzi@unimore.it" class="auth_mail" title="E-mail the corresponding author} ; Paola Gambarelli

关键词：Surrogate model ; Evolutionary algorithm ; Model updating ; Differential evolution ; Infill sampling strategy

刊名：Computers & Structures

出版年：2017

5.Microgrid sizing with combined evolutionary algorithm and MILP unit commitment

作者：Bei Li^a ; ^{bei.li@utbm.fr} ; Robin Roche^a ; ^{robin.roche@utbm.fr} ; Abdellatif Miraoui^b ; ^{abdellatif.miraoui@utbm.fr}

关键词：Energy management ; Evolutionary algorithm ; Microgrid ; Sizing ; Unit commitment

刊名：Applied Energy

出版年：2017

6.Hybrid evolutionary algorithm with extreme machine learning fitness function evaluation for two-stage capacitated facility location problems

作者：Peng Guo^a ; ^{pengguo318@gmail.com} ; Wenming Cheng^a ; ^{wmcheng@swjtu.edu.cn} ; Yi Wang ; ^b ; ^{ywang2@aum.edu}

关键词：Facility location ; Evolutionary algorithm ; Fitness approximation ; Local search ; Extreme machine learning

刊名：Expert Systems with Applications

出版年：2017

7.Reservoir flood control operation using multi-objective evolutionary algorithm with decomposition and preferences

作者：Yutao Qi^a ; ^{qi_yutao@163.com} ; Jusheng Yu^a ; Xiaodong Li^b ; Yanxi Wei^a ; Qiguang Miao^a

关键词：Reservoir flood control operation ; Multi-objective evolutionary algorithm ; MOEA/D ; Preference

刊名：Applied Soft Computing

出版年：2017

8.Crashworthiness optimization of thin-walled tubes using Macro Element Method and Evolutionary Algorithm

作者：Mariusz Pyrz ; ^{mpyrz@simr.pw.edu.pl} ; Marek Krzywoblocki ^{mkrzywoblocki@simr.pw.edu.pl}

关键词：Crashworthiness ; Energy absorbing tubes ; Macro Element Method ; Optimization ; Evolutionary algorithm ; Monte-Carlo method

刊名：Thin-Walled Structures

出版年：2017

9.Hybrid evolutionary approaches for the single machine order acceptance and scheduling problem

作者：Sachchida Nand Chaurasia ^{mc10pc13@uohyd.ernet.in} ; Alok Singh ; ^{alokcs@uohyd.ernet.in}

关键词：Steady-state genetic algorithm ; Estimation of distribution algorithm ; Evolutionary algorithm ; Guided mutation ; Order acceptance and scheduling ; Single machine scheduling ; Sequence dependent setup time

刊名：Applied Soft Computing

出版年：2017

10.An improved evolutionary algorithm for handling many-objective optimization problems

作者：S. Mohammadi ; MSc^a ; ^{samane_mohammadi20@yahoo.com} ; M.A.S. Monfared^a ; ^{mas_monfared@alzahra.ac.ir} (Associate Professor) ; M. Bashiri^b ; ^{bashiri.m@gmail.com} (Associate Professor)

关键词：Many-objective optimization ; Reference point ; Evolutionary algorithm ; NSGA-II

刊名：Applied Soft Computing

出版年：2017

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