仿生优化算法研究进展

N. Pazhaniraja, P. V. Paul, G. Roja, K. Shanmugapriya, B. Sonali
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引用次数: 18

摘要

生物激励是一个将连接主义、工程学、社会行为和涌现等相关的子领域结合在一起的研究领域。受生物启发的计算是自然计算的一个主要子集。仿生算法是一种有效的优化算法。由于现有的生物启发算法可以解决问题,基于人类、黑猩猩和海豚等智能动物的算法可以以最有效和优化的方式解决问题。海豚是最聪明的动物之一,能有效地解决复杂的问题。本文解释了各种基于群的优化算法,帮助我们分析这些算法可以在哪里有效地应用。本文从定义、提出的模型、实验评价和各自的优势等方面简要介绍了文献综述。
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A study on recent bio-inspired optimization algorithms
Bio-Inspired is a field of study that combines all the subfields together which are related to the connectionism, engineering, social behavior and emergence. Biologically inspired computing is a major subset of natural computation. The bio inspired algorithm is an effective optimization algorithm. Since the existing bio inspired algorithms can be solve the problems, an algorithm based on intelligent animals like Human, Chimpanzee and Dolphin can solve the problems in most efficient and optimized way. Dolphin is one of the most intelligent animal which can solve the complex problems in an efficient manner. This paper explains about the various swarm based optimization algorithms which helps us to analyze where these algorithms can be applied in an efficient manner. A survey on various papers is briefly explained with respect to definition, proposed model, experimental evaluation and their advantages.
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