Ant Colony Algorithms for Steiner Trees

Author:

Singh Gurdip1,Das Sanjoy1,Gosavi Shekhar V.1,Pujar Sandeep1

Affiliation:

1. Kansas State University, USA

Abstract

This chapter introduces ant colony optimization as a method for computing minimum Steiner trees in graphs. Tree computation is achieved when multiple ants, starting out from different nodes in the graph, move towards one another and ultimately merge into a single entity. A distributed version of the proposed algorithm is also described, which is applied to the specific problem of data-centric routing in wireless sensor networks. This research illustrates how tree based graph theoretic computations can be accomplished by means of purely local ant interaction. The authors hope that this work will demonstrate how innovative ways to carry out ant interactions can be used to design effective ant colony algorithms for complex optimization problems.

Publisher

IGI Global

Cited by 9 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. BCLO—Brainstorming and Collaborative Learning Optimization Algorithms;Machine Learning Paradigms: Theory and Application;2018-12-08

2. A Population-based Local Search Technique with Random Descent and Jump for the Steiner Tree Problem in Graphs;Proceedings of the Genetic and Evolutionary Computation Conference 2016;2016-07-20

3. An Ant-Routing Algorithm for Wireless Sensor Networks;Lecture Notes in Electrical Engineering;2011

4. ACO Based Energy-Balance Routing Algorithm for WSNs;Lecture Notes in Computer Science;2010

5. Swarm Intelligence Inspired Multicast Routing: An Ant Colony Optimization Approach;Lecture Notes in Computer Science;2009

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