...
首页> 外文期刊>Expert systems with applications >Potential offspring production strategies: An improved genetic algorithm for global numerical optimization
【24h】

Potential offspring production strategies: An improved genetic algorithm for global numerical optimization

机译:潜在的后代生产策略:用于全局数值优化的改进遗传算法

获取原文
获取原文并翻译 | 示例
   

获取外文期刊封面封底 >>

       

摘要

In this paper, a sharing evolution genetic algorithms (SEGA) is proposed to solve various global numerical optimization problems. The SEGA employs a proposed population manager to preserve chromosomes which are superior and to eliminate those which are worse. The population manager also incorporates additional potential chromosomes to assist the solution exploration, controlled by the current solution searching status. The SEGA also uses the proposed sharing concepts for cross-over and mutation to prevent populations from falling into the local minimal, and allows GA to easier find or approach the global optimal solution. All the three parts in SEGA, including population manager, sharing cross-over and sharing mutation, can effective increase new born offspring's solution searching ability. Experiments were conducted on CEC-05 benchmark problems which included unimodal, multi-modal, expanded, and hybrid composition functions. The results showed that the SEGA displayed better performance when solving these benchmark problems compared to recent variants of the genetic algorithms.
机译:本文提出了一种共享进化遗传算法(SEGA)来解决各种全局数值优化问题。 SEGA雇用了一个建议的种群管理器来保存优势染色体,并消除劣势的染色体。种群管理器还合并了其他潜在的染色体,以协助溶液的探索(受当前溶液搜索状态控制)。 SEGA还使用建议的共享概念进行交叉和变异,以防止种群陷入局部极小值,并使GA可以更轻松地找到或接近全局最优解。 SEGA中的所有三个部分,包括种群管理器,共享交叉和共享突变,都可以有效地提高新生后代的解决方案搜索能力。针对CEC-05基准问题进行了实验,这些问题包括单峰,多峰,扩展和混合组成函数。结果表明,与遗传算法的最新变体相比,SEGA在解决这些基准问题时表现出更好的性能。

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