Binary ant colony evolutionary algorithm

Abstract

Every insect is considered, from the viewpoint of biological evolution, to be a neural cell that constitutes a neural network in a casual and loose way of joint. Through simulating the ant swarm intelligence on the basis of human neural network, this paper advances a linear binary network. The binary code expects a low intelligence of each ant, and each path corresponds to a comparatively small storage space, thus considerably improving the efficiency of computation. The test of function optimization and multi-dimensional 0/1 Knapsack proves that the computation has a good speed of convergence, a high stability and a perfect solution.