Surrogate Model-based Evaluation Strategy with Non-random Selection of Substituted Individuals

CHENG Jian; GUO Yi-nan; GONG Dun-wei; QIAN Jian-sheng

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Surrogate Model-based Evaluation Strategy with Non-random Selection of Substituted Individuals

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- Surrogate Model-based Evaluation Strategy with Non-random Selection of Substituted Individuals
- Acta Electronica Sinica Vol. 37, Issue 1, Pages: 190-194(2009)
- 作者机构：
  
  中国矿业大学信息与电气工程学院,江苏,徐州,221008
- 作者简介：
- 基金信息：
- DOI：
  CLC： TP301
- Published：2009
- 稿件说明：
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CHENG Jian, GUO Yi-nan, GONG Dun-wei, et al. Surrogate Model-based Evaluation Strategy with Non-random Selection of Substituted Individuals[J]. Acta Electronica Sinica, 2009, 37(1): 190-194.
DOI：

CHENG Jian, GUO Yi-nan, GONG Dun-wei, et al. Surrogate Model-based Evaluation Strategy with Non-random Selection of Substituted Individuals[J]. Acta Electronica Sinica, 2009, 37(1): 190-194. DOI：

摘要

代理模型评价策略是解决交互式遗传算法中人疲劳这一瓶颈问题的主要手段.每代中代理模型评价个体选择不同

将导致不同的算法性能

甚至算法不收敛.针对该问题

提出基于样本聚类的非随机替代个体选择策略.给出广义近似距离、类近似距离和中心近似距离三种判断个体所属类的距离度量.面向服装进化设计系统实例

仿真结果表明非随机选择比随机选择在统计意义上具有更好的稳定性

可以有效避免个体选择不良误导进化过程.

Abstract

Surrogate model-based evaluation strategy is a main method aiming at solving human fatigue in interactive genetic algorithms.Different substituted individuals are selected in surrogate evaluation strategy will lead to different performance

even divergence.To solve the problem

non-random selection method of substituted individuals based on clustering is proposed.Three kinds of distance

including generalized approximate distance

clustering approximate distance and center approximate distance

are given so as to judge which class individuals belong to.Taking fashion evolutionary design system as an example

simulation results indicate the methods have better stability than random selection method.They effectively avoid misguiding evolutionary process caused by irrational selection.

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