Ant algorithm is a novel meta-heuristic optimization algorithm, but at the same time there are some disadvantages. This paper proposed an ant colony algorithm with route evaluation based on the basic ant colony algorithm. After all ant complete the route search once, the current search situation can be evaluated according to an improved formula of standard deviation, then to decide to update gl...

Routing in dynamic network is a challenging one, because the topology of the network is not fixed. This issue is addressed in this presentation using ant algorithm to explore the network using intelligent packets. The paths generated by ants are given as input to genetic algorithm. The genetic algorithm finds the set of optimal routes. The importance of using ant algorithm is to reduce the size...

Many methods currently used in combinatorial optimization are inspired by adaptative natural behaviors or natural systems, e.g. hill-climbing local search, genetic algorithms, simulated annealing, : : : These heuristics provide some very good results, even when the problem size makes it impossible to use more traditional exact methods (such as branch and bound, ...). Ants system algorithms belo...

Ant Colony Optimization (ACO) [31, 32] is a recently proposed metaheuristic approach for solving hard combinatorial optimization problems. The inspiring source of ACO is the pheromone trail laying and following behavior of real ants which use pheromones as a communication medium. In analogy to the biological example, ACO is based on the indirect communication of a colony of simple agents, calle...

Ant colony optimization (ACO) is the algorithm that has inspired from natural behavior of ants life, which the ants leaved pheromone to search food on the ground. In this paper, ACO is introduced for resolving the edge detection in the biomedical image. Edge detection method based on ACO is able to create a matrix pheromone that shows information of available edge in each location of edge pixel...

Motifs (patterns, signatures, domains) are useful to determine nucleotides/amino-acids that are likely involved in structures, functions, regulations and evolutions, or to infer homology between genes/proteins. The main objective of this paper is the fusion of motifs. Our task is to analyze a set of possible motifs and to detect if similarity exists between them, to construct a general motif. T...

We present in this paper, a new model for document hierarchical clustering, which is inspired from the self-assembly behavior of real ants. We have simulated the way ants build complex structures with different functions by connecting themselves to each other. Ants may thus build ”chains of ants” or form ”drops of ants”. The artificial ants that we have defined will similarly build a tree. Each...

The Argentine ant (Linepithema humile) is an invasive species that disrupts the balance of natural ecosystems by displacing indigenous ant species throughout its introduced range. Previous studies that examined the mechanisms by which Argentine ants attain ecological dominance showed that superior interference and exploitation competition are key to the successful displacement of native ant spe...

The Active Nodal Task Seeking (ANTS) approach to the design of multicom-puter systems is named for its basic component: an Active Nodal Task-Seeker (ANT). In this system, there is no load balancing or load sharing, instead, each ANT computing node is actively nding out how it can contribute to the execution of the needed tasks. A run-time partition is established such that some of the ANT compu...

Many real world problems can be modelled as an optimization problem. Evolutionary algorithms are used to solve these problems. Ant colony algorithm is a class of evolutionary algorithms that have been inspired of some specific ants looking for food in the nature. These ants leave trail pheromone on the ground to mark good ways that can be followed by other members of the group. Ant colony optim...