Hybrid algorithm for ant colony optimization based on chaos technique

In order to improve the solving performance of ant colony optimization (ACO), first the ACO method dealing with continuous variables is analyzed and mapping rules for two types of chaos map are given. Next, ACO based on Logistic map (LM-ACO) and Henon map (HM-ACO) are constructed, and a method which adopts k mean-square-root envelope function to reduce and smooth multi-constraints is given. To evaluate the performance of LM-ACO, HM-ACO and the ACO, the three methods are used to solve the pressure vessel constrained optimal problem. Their performances are compared in terms of optimal solution, iterative occupancy hours and so on. Comparison results indicate that the HM-ACO has many advantages such as higher solution accuracy and higher computational efficiency.