Analysis of various swarm-based & ant-based algorithms

A. Gupta, A. Verma, H. Sadawarti
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引用次数: 12

Abstract

Ant algorithms and swarm intelligence systems have been offered as a novel computational approach that replaces the traditional emphasis on control, preprogramming and centralization with designs featuring autonomy, emergence and distributed functioning. These designs provide scalable, flexible and robust, able to adapt quickly changes to changing environments and to continue functioning even when individual elements fail. These properties make swarm intelligence very attractive for mobile ad hoc networks. These algorithms also provide potential advantages for conventional routing algorithms. Ant Colony Optimization is popular among other Swarm Intelligence Techniques.In this paper a detailed comparison of different Ant based algorithms is presented. The comparative results will help the researchers to understand the basic differences among various existing Ant colony based routing algorithms.
各种基于群算法和基于蚁算法的分析
蚂蚁算法和群体智能系统作为一种新颖的计算方法,取代了传统的控制、预编程和集中的设计,具有自主性、涌现性和分布式功能。这些设计提供了可扩展、灵活和健壮的功能,能够快速适应不断变化的环境,即使单个元素失效也能继续运行。这些特性使得群体智能对移动自组织网络非常有吸引力。这些算法也为传统的路由算法提供了潜在的优势。蚁群优化是群体智能技术中比较流行的一种。本文对不同的基于Ant的算法进行了详细的比较。比较结果将有助于研究人员了解现有各种基于蚁群的路由算法之间的基本差异。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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