ANT COLONY SYSTEM WITH STATE TRANSITION

Sri Vasavi College, Erode Self-Finance Wing 3rd February 2017 National Conference on Computer and Communication NCCC’17

Format: Volume 5, Issue 1, No 12, 2017

Copyright: All Rights Reserved ©2017

Year of Publication: 2017

Author: Mrs. K. Sathya Sundari

Reference:IJCS-211

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Abstract

Ant Colony System (AS) is a first member of algorithms inspired by behavior of real ants. Ant System (AS) is being the prototype of a number of ant algorithms, which collectively implement ACO paradigm. ACS makes (i) State transition, (ii) Pheromone updating .

References

1. Dorigo,M. andGambardella, L. (1997). AntColony System: A Cooperative Learning Approach to the Traveling Salesman Problem. 2. Dorigo, M., Maniezzo, V., and Colorni, A. (1996). The Ant System: Optimization by a Colony of Cooperating Agents. 3. Dorigo et al (1991). Ant Colony System: Cooperative Learning Approach to the Traveling Salesman Problem. 4. Colorni, A., Dorigo,M., Maniezzo, V., and Trubian,M. (1994). Ant System for Job-Shop Scheduling. Belgian Journal of Operations Research, Statistics and Computer Science, 34(1):39–53. 5. Watkins and Dayan 1992. Ant Colony System:Q-Learning. 6. Gambardella and Dorigo (1995), The Ant System: Optimization by a Colony of Cooperating Agents 7. Reinelt 1994. Data structure Learning Approach to the Traveling Salesman Problem.


Keywords

AS, ACO

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