|Table of Contents|

Interval Discrete Genetic Algorithms Based on FastTwo-Level Solution Repair Strategy(PDF)

《南京师大学报（自然科学版）》[ISSN:1001-4616/CN:32-1239/N]

Issue:
2019年03期
Page:
73-79
Research Field:
·全国机器学习会议论文专栏·
Publishing date:

Info

Title:
Interval Discrete Genetic Algorithms Based on FastTwo-Level Solution Repair Strategy
Author(s):
Li Erchao; Ma Yuquan
College of Electrical and Information Engineering,Lanzhou University of Technology,Lanzhou 730050,China
Keywords:
multi-objective optimization; interval discrete variables; genetic algorithm; fast two-level repair; constraints
PACS:
TP273
DOI:
10.3969/j.issn.1001-4616.2019.03.010
Abstract:
A fast two-level solution repair strategy is proposed for interval discrete multi-objective optimization problem with equality constraints. The main idea is:first,a population satisfying equality constraints is generated by using the initial solution generator,and then,the repairable individuals in this population are repaired to definitions by taking the minimum degree of violation of constraints as the objective function. In the interval,finally,the individual satisfying the constraints can be fine-tuned in the definition sub-interval. The adjusting method is as follows:according to the proportion of the upper and lower limits of each variable in the current individual in its interval,the variable that does not satisfy the equality constraints can be effectively repaired by adjusting the proportion of the upper and lower limits of the individual in the total adjustable upper and lower limits. Finally,the effectiveness of the proposed algorithm is verified by experiments.

References:

[1] 侯伟. 基于多目标优化算法的动压滑动轴承设计[J]. 控制工程,2018,25(6):1044-1049.
[2]朱光宇,徐文婕. 考虑能耗与质量的机床构件生产线多目标柔性作业车间调度方法[J]. 控制与决策,2019,34(2):252-260.
[3]王嵘冰,徐红艳,郭军. 自适应的非支配排序遗传算法[J]. 控制与决策,2018,33(12):2191-2196.
[4]栗三一,李文静,乔俊飞. 一种基于密度的局部搜索NSGA2算法[J]. 控制与决策,2018,33(1):60-66.
[5]侯莹,韩红桂,乔俊飞. 基于参数动态调整的多目标差分进化算法[J]. 控制与决策,2017,32(11):1985-1990.
[6]郑金华. 多目标进化算法及其应用[M]. 北京:科学出版社,2007.
[7]BALRAM S. Study of simulated annelaling based algorithms for multi-objective optimization of constrained problem[J]. Computers and chemical engineering,2004,28:1849-1872.
[8]TAYSI N,GOGUS M T,OZAKEA M. Optimization of arches using genetic algorithm[J]. Computer Optim Appl,2008,41:378-383.
[9]刘松兵. 面向多目标优化的群智能算法研究[D]. 长沙:湖南大学,2009.
[10]贾婷芳,张学良. 离散多目标优化算法的研究[J]. 机械工程与自动化,2011,5:206-208.
[11]苏凯,刘吉臻,牛玉广,等. 一类解修补方法在厂级负荷优化分配中的应用[J]. 华北电力大学学报,2012,39(3):71-77.
[12]SUSHIL K R N. Nonconvex economic load dispatch using an efficient real-coded genetic algorithm[J]. Applied soft computing,2009,9(1):169-176.
[13]贾江涛,管晓宏,翟桥柱. 考虑水头影响的梯级水电站群短期优化调度[J]. 电力系统自动化,2009,33(13):7-13.
[14]BAUMRUCKER B T. Mathematical programs with equilibrium constraint(MPECs)in process systems engineering[D]. Pittsburgh:Carnegie Mellon University,2009:1-26.
[15]ZHI Q,LUO J S P,Daniel R. Mathematical programs with equilibrium constraints[M]. Cambridge:The Press Syndicate of the University of Cambridge,1996:5-16.

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Last Update: 2019-09-30