...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>International Journal of Intelligent Computing and Cybernetics >High-dimensional real-parameter optimization using the differential ant-stigmergy algorithm
【24h】

High-dimensional real-parameter optimization using the differential ant-stigmergy algorithm

机译：使用差分蚁群算法的高维实参数优化

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Purpose - The purpose of this paper is to present an algorithm for global optimization of high-dimensional real-parameter cost functions. Design/methodology/approach - This optimization algorithm, called differential ant-stigmergy algorithm (DASA), based on a stigmergy observed in colonies of real ants. Stigmergy is a method of communication in decentralized systems in which the individual parts of the system communicate with one another by modifying their local environment. Findings - The DASA outperformed the included differential evolution type algorithm in convergence on all test functions and also obtained better solutions on some test functions. Practical implications - The DASA may find applications in challenging real-life optimization problems such as maximizing the empirical area under the receiver operating characteristic curve of glycomics mass spectrometry data and minimizing the logistic leave-one-out calculation measure for the gene-selection criterion. Originality/value - The DASA is one of the first ant-colony optimization-based algorithms proposed for global optimization of the high-dimensional real-parameter problems.
机译：目的-本文的目的是提出一种用于高维实参数成本函数的全局优化的算法。设计/方法/方法-这种优化算法称为差分蚂蚁抗扰度算法（DASA），基于在真实蚂蚁菌落中观察到的抗扰度。 Stigmergy是分散系统中的一种通信方法，其中系统的各个部分通过修改其本地环境相互通信。研究结果-DASA在所有测试功能的收敛性方面均优于包含的差分进化类型算法，并且在某些测试功能上也获得了更好的解决方案。实际意义-DASA可能会应用于现实生活中的优化难题，例如，使糖组学质谱数据的接收器工作特征曲线下的经验区域最大化，以及针对基因选择标准的逻辑后遗忘式计算方法最小化。原创性/价值-DASA是最早针对高维实参数问题进行全局优化的基于蚁群优化的算法之一。

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