不同类型进化算法的竞争比较

是 否 +2 论坛币

k人 参与回答

经管之家送您一份

应届毕业生专属福利!

求职就业群

赵安豆老师微信：zhaoandou666

经管之家联合CDA

送您一个全额奖学金名额~ !

立即领取

感谢您参与论坛问题回答

经管之家送您两个论坛币！

+2 论坛币

摘要翻译：
本文比较了作者在前人的工作中为解决土木工程中的一些问题而提出的几种随机优化算法。介绍的优化方法有：整数增广模拟退火(IASA)、实数编码增广模拟退火(RASA)、由R.Storn和K.Price提出的原始差分进化(DE)和简化实数编码差分遗传算法(SADE)。每一种方法都是针对特定的优化问题提出的；即Chebychev试验多项式问题、所谓的0型函数和两个工程问题--钢筋混凝土梁布置和周期单胞问题。详细而广泛的数值试验检验了所提算法的稳定性和效率。实验结果表明，RASA、IASA和SADE算法的性能和鲁棒性相当，而DE算法的性能稍差。这一事实加上少量的内部参数使SADE方法成为实际应用中最鲁棒的方法。
---
英文标题：
《A competitive comparison of different types of evolutionary algorithms》
---
作者：
O. Hrstka, A. Kucerova, M. Leps and J. Zeman
---
最新提交年份：
2009
---
分类信息：

一级分类：Computer Science        计算机科学
二级分类：Neural and Evolutionary Computing        神经与进化计算
分类描述：Covers neural networks, connectionism, genetic algorithms, artificial life, adaptive behavior. Roughly includes some material in ACM Subject Class C.1.3, I.2.6, I.5.
涵盖神经网络，连接主义，遗传算法，人工生命，自适应行为。大致包括ACM学科类C.1.3、I.2.6、I.5中的一些材料。
--
一级分类：Computer Science        计算机科学
二级分类：Artificial Intelligence        人工智能
分类描述：Covers all areas of AI except Vision, Robotics, Machine Learning, Multiagent Systems, and Computation and Language (Natural Language Processing), which have separate subject areas. In particular, includes Expert Systems, Theorem Proving (although this may overlap with Logic in Computer Science), Knowledge Representation, Planning, and Uncertainty in AI. Roughly includes material in ACM Subject Classes I.2.0, I.2.1, I.2.3, I.2.4, I.2.8, and I.2.11.
涵盖了人工智能的所有领域，除了视觉、机器人、机器学习、多智能体系统以及计算和语言（自然语言处理），这些领域有独立的学科领域。特别地，包括专家系统，定理证明（尽管这可能与计算机科学中的逻辑重叠），知识表示，规划，和人工智能中的不确定性。大致包括ACM学科类I.2.0、I.2.1、I.2.3、I.2.4、I.2.8和I.2.11中的材料。
--

---
英文摘要：
  This paper presents comparison of several stochastic optimization algorithms developed by authors in their previous works for the solution of some problems arising in Civil Engineering. The introduced optimization methods are: the integer augmented simulated annealing (IASA), the real-coded augmented simulated annealing (RASA), the differential evolution (DE) in its original fashion developed by R. Storn and K. Price and simplified real-coded differential genetic algorithm (SADE). Each of these methods was developed for some specific optimization problem; namely the Chebychev trial polynomial problem, the so called type 0 function and two engineering problems - the reinforced concrete beam layout and the periodic unit cell problem respectively. Detailed and extensive numerical tests were performed to examine the stability and efficiency of proposed algorithms. The results of our experiments suggest that the performance and robustness of RASA, IASA and SADE methods are comparable, while the DE algorithm performs slightly worse. This fact together with a small number of internal parameters promotes the SADE method as the most robust for practical use.
---
PDF链接：
https://arxiv.org/pdf/0902.1647

扫码加我 拉你入群

请注明：姓名-公司-职位

以便审核进群资格，未注明则拒绝

分享0 收藏0 回帖

关键词：进化算法 simulated 试验 methods 进化 RASA