Intellectual Behavior of a Group of Wild Animals: A Computational Intelligence Study
Avtar Singh Buttar1, Ashok Kumar Goel2, Shakti Kumar3
1Avtar Singh Buttar, Department of Electronics and Communication Engg. Punjab Technical University, Jalandhar-Kapurthala Highways India.
2Ashok Kumar Goel, Director, Maharaja Agrasen University, Baddi, Solan (HP), India.
3Shakti Kumar, Chairman, Institute of Science and Technology, Kalawad (Haryana) India.
Manuscript received on February 04, 2013. | Revised Manuscript received on February 27, 2013. | Manuscript published on March 05, 2013. | PP: 127-132 | Volume-3 Issue-1, March 2013. | Retrieval Number: A1316033113/2013©BEIESP
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Numerous methodologies have been invented inspired by nature and based on real life behavior of species which perform task in a group. In this paper, a novel methodology based on intelligent chasing and hunting methods adopted by the animals in a group to chase & hunt their prey is presented. The dog is taken as prime model for developing the methodology. The method is named as “Dog Group Wild Chase & Hunt Drive (DGCHD) . The algorithm is implemented on Traveling Salesman benchmark problem available in literature. The problem has been solved by different researchers for testing their proposed novel intelligent algorithms in various nature inspired technologies such as Ant Colony System, Genetic Algorithms etc. The results obtained are very optimistic and encouraging.
Keywords: Dogs behavior, Chasing & hunting, Computational Intelligence, Dog Group Wild Chase & Hunt Drive (DGCHD), combinatorial optimization.