【24h】

The pareto differential evolution algorithm

机译:帕雷托差分进化算法

获取原文
获取原文并翻译 | 示例
           

摘要

The use of evolutionary algorithms (EAs) to solve problems with multiple objectives (known as Vector Optimizetion Problems (VOPs)) has attracted much attention recently. Being population based approaches, EAs offer a means to find a group of pareto-optimal solutions in a single run. Differential Evolution (DE) is an EA that was developed to handle optimization problems over continuous domains. The objective of this paper is to introduce a novel Pareto Differential Evolution (PDE) algorithm to solve VOPs. The solutions provided by the proposed algorithm for five standard test problems is competitive to nine known evolutionary multiobjective algorithms for solving VOPs.
机译:进化算法(EA)用来解决具有多个目标的问题(称为向量优化问题(VOP))最近引起了很多关注。作为基于人口的方法,EA提供了一种方法,可以在一次运行中找到一组最优的解决方案。差分进化(DE)是一种EA,旨在处理连续域中的优化问题。本文的目的是介绍一种新颖的帕累托差分演化(PDE)算法来求解VOP。所提出的算法为五个标准测试问题提供的解决方案与九种已知的解决VOP的进化多目标算法相比具有竞争力。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号