As the sports training predicting model based on chaos local predicting method still has the low predicting accuracy and the slow function speed problems, this paper proposes a sports training chaos predicting model based on weight control ant colony algorithm. It firstly uses the comprehensive weight factor to perform the weight control to the initial information of the new join node in the an...

This work introduces ANB (Ant Algorithm for Non-Bifurcated Flows), a novel approach to capacitated static optimization of flows in connection-oriented computer networks. The problem considered arises naturally from several optimization problems that have recently received significant attention. The proposed ANB is an ant algorithm motivated by recent works on the application of the ant algorith...

Form the view of the biological viewpoint; each ant of social insects is regarded as neuron. They compose a neural network by stochastic and loose connections with each other; Similar to the artificial neural network simulating the ant colony, the Ant colony algorithm of binary network is presented. As the binary coding is adapted, lower aptitude behave of single ant is requested, less storage ...

Ant colony optimization and artificial potential field were used respectively as global path planning and local path planning methods in this paper. Some modifications were made to accommodate ant colony optimization to path planning. Pheromone generated by ant colony optimization was also utilized to prevent artificial potential field from getting local minimum. Simulation results showed that ...

An innovative ant colony algorithm called memory-based ant colony algorithm is proposed to solve the bipartite subgraph problem. In the proposed algorithm, artificial ant has memory of solution found previously, and can use it to construct a new solution. Besides, in the proposed algorithm two kinds of pheromone and two kinds of heuristic information are also adopted to reinforce the search abi...

This study proposes an Ant Colony Optimization using Genetic Information (GIACO). The GIACO algorithm combines Ant Colony Optimization (ACO) with Genetic Algorithm (GA). GIACO searches solutions by using the pheromone of ACO and the genetic information of GA. In addition, two kinds of ants coexist: intelligent ant and dull ant. The dull ant is caused by the mutation and cannot trail the pheromo...

We present two heuristic mesh-partitioning methods, both of which build on the multiple ant-colony algorithm in order to improve the quality of the mesh partitions. The first method augments the multiple ant-colony algorithm with a multilevel paradigm, whereas the second uses the multiple ant-colony algorithm as a refinement to the initial partition obtained by vector quantization. The two meth...

With the speeding up of urbanization in our country, the situation of urban emergency is getting more and more serious; therefore, it is necessary to promote the study in urban emergency management, so as to enhance the city ability of resisting the emergency. Based on the defects of the emergency vehicle routing choosing, the paper puts forward a particle swarm optimization based ant colony al...

This paper introduces the basic theory and procedure for working out solutions of ant colony genetic algorithm, describes optimization, constraints and objectives of construction project scheduling, then establishes basic model for scheduling optimization of construction project, and put forward improved ant colony genetic algorithm for solving the basic model. Performance of ant colony genetic...