Swarm intelligence: from natural to artificial systems
Swarm intelligence: from natural to artificial systems
Future Generation Computer Systems
Ant Colony Optimization
ISDA '06 Proceedings of the Sixth International Conference on Intelligent Systems Design and Applications - Volume 01
Ant colony system: a cooperative learning approach to the traveling salesman problem
IEEE Transactions on Evolutionary Computation
New directions in cryptography
IEEE Transactions on Information Theory
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The ability of ant colonies to form paths for carrying food is rather fascinating. The problem is solved collectively by the whole colony. This ability is explained by the fact that ants communicate in an indirect way by laying trails of pheromone. The higher the pheromone trail within a particular direction, the higher the probability of choosing this direction. The collective problem solving mechanism has given rise to a metaheuristic referred to as Ant Colony Optimization. On this work we use intoitionistic fuzzy estimation of start nodes with respect to the quality of the solution. Various start strategies are offered. Sensitivity analysis of the algorithm behavior according to estimation parameters is made. As a test problem Multidimensional (Multiple) Knapsack Problem is used.