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...

The basic ant colony algorithm in the welding robot path planning, in the search process, prone to search for too long, low efficiency, easy to fall into the local optimal and other issues. In this paper, the basic ant colony algorithm is improved, and the Adadelta algorithm is introduced. By combining the basic ant colony algorithm and Adadelta algorithm, the probability of selecting the next ...

In view of shortcomings of BP neural network, which is slow to converge and tends to trap in local optimum when applied in fault diagnosis, an approach for fault diagnosis based on BP neural network optimized by chaos ant colony algorithm is proposed. Mathematical model of chaos ant colony algorithm is created. Real-coded method is adopted and the weights and thresholds of BP neural network are...

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 ...

The basic ant colony algorithm for mobile robot path planning has many problems, such as lack of stability,algorithm premature convergence, more difficult to find optimal solution for complex problems and so on. This paper proposes four improvement measures. 1. Apply genetic algorithm to optimization and configuration parameters of the basic ant colony algorithm; 2. Apply max min ant method to ...

Various studies have shown that the ant colony optimization (ACO) algorithm has a good performance in approximating complex combinatorial problems such as traveling salesman problem (TSP) for real-world applications. However, disadvantages long running time and easy stagnation still restrict its further wide application many fields. In this study, saltatory evolution (SEACO) is proposed to incr...

Ant colony algorithm, a heuristic simulated algorithm, provides better solutions for non-convex, non-linear and discontinuous optimization problems. For ant colony algorithm, it is frequently to be trapped into local optimum, which might lead to stagnation. This article presents the city-select strategy, local pheromone update strategy, optimum solution prediction strategy and local optimizatio...

Context: Emergence is a term used to describe complex patterns or systems which are formed from very basic rules or agents. Once such example which has intrigued scientists across several fields has been ant colonies. Computer scientists are particularly interested in ant colonies as although each individual ant acts in a very simple manor, the ant colony as a whole is able to find shortest pat...

in this paper, a multi-objective reconfiguration problem has been solved simultaneously by a modified ant colony optimization algorithm. two objective functions, real power loss and energy not supplied index (ens), were utilized. multi-objective modified ant colony optimization algorithm has been generated by adding non-dominated sorting technique and changing the pheromone updating rule of ori...