ANT COLONY SYSTEM WITH STATE TRANSITION

Sri Vasavi College, Erode Self-Finance Wing, 3rd February 2017. National Conference on Computer and Communication, NCCC’17. International Journal of Computer Science (IJCS) Published by SK Research Group of Companies (SKRGC)

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