Chaotic Artificial Bee Colony Hybrid Discrete Constrained Optimization Algorithm

Swarm intelligence is a research branch that models the population of interacting agents or swarms that are able to self-organize. An ant colony, a flock of birds or an immune system is a typical example of a swarm system. Bees’ swarming around their hive is another example of swarm intelligence. The Artificial Bee Colony algorithm is an optimization algorithm based on the intelligent behavior of honey bee swarm. This paper presents Bee Swarm Optimization intended to introduce chaotic sequences into the algorithm. On the basis of Artificial Bee Colony Optimization Algorithm, a new algorithm by introducing constructing dynamic penalty function and chaotic sequences was presented. Based on Matlab software, the program CABC1.0 with hybrid discrete variables for the proposed algorithm was developed. The complex examples are given. The results show that this algorithm has no special requirements on the characteristics of optimal designing problems, which has a fairly good universal adaptability and a reliable operation of program with a strong ability of overall convergence.