This research applies the meta-heuristic method of ant colony optimization (ACO) to an established set of vehicle routing problems (VRP). The procedure simulates the decision-making processes of ant colonies as they forage for food and is similar to other adaptive learning and artificial intelligence techniques such as Tabu Search, Simulated Annealing and Genetic Algorithms. Modifications are m...

In the rapid increasing usage of wireless sensor networks, fault tolerance is an exigent task to improve the overall performance. In this work we made an attempt using artificial bee colony approach to find data aggregation with fault tolerance in WSN to make an effective use of the existing resources. In this paper it is tried to apply the performance of the Q-MST based fault tolerance mechani...

ant colony optimisation (aco) algorithm and adaptive refinement mechanism are used in this paper for solution of optimization problems. many of the real engineering problems are، however، of continuous nature and finding their solution by discrete ant based algorithms requires discretisation of the decision variables in which affected the convergence and performance of the algorithm. in this pa...

Wireless Sensor Networks are the new generation of networks that typically are formed great numbers of nodes and the communications of these nodes are done as Wireless. The main goal of these networks is collecting data from neighboring environment of network sensors. Since the sensor nodes are battery operated and there is no possibility of charging or replacing the batteries, the lifetime of ...

in this paper, a new continuous ant colony optimization (caco) algorithm is proposed for optimal reservoir operation. the paper presents a new method of determining and setting a complete set of control parameters for any given problem, saving the user from a tedious trial and error based approach to determine them. the paper also proposes an elitist strategy for caco algorithm where best solut...

nowadays, software cost estimation (sce) with machine learning techniques are more performance than other traditional techniques which were based on algorithmic techniques. in this paper, we present a new hybrid model of multi-layer perceptron (mlp) artificial neural network (ann) and ant colony optimization (aco) algorithm for high accuracy in sce called multilayer perceptron ant colony optimi...

Ant miner algorithm is used to find the classification rule which helps to do classification of the data. Ant miner uses the Ant Colony Optimization (ACO) which deals with artificial systems that is inspired from the foraging behavior of real ants. Here the task is to improve the pheromone update method in the current system. Pheromone updating is dependent mainly on the initial pheromone of th...

wireless sensor networks are the new generation of networks that typically are formed great numbers of nodes and the communications of these nodes are done as wireless. the main goal of these networks is collecting data from neighboring environment of network sensors. since the sensor nodes are battery operated and there is no possibility of charging or replacing the batteries, the lifetime of ...

In order to improve the efficiency and adaptability of cognitive radar jamming decision-making, a fusion algorithm (Ant-QL) based on ant colony Q-Learning is proposed in this paper. The does not rely priori information enhances through real-time interactions between jammer target radar. At same time, it can be applied single multiple countermeasure scenarios with high effects. First, traditiona...