A hybrid Ant Colony and Genetic Algorithm for Topology Optimization of Two-Dimensional Continuous Environments

In this paper ant colony algorithm as an approach based on collective intelligence is modified in combination with genetic algorithm and will be used for topology optimization of 2D continuous environments. This approach is inspired by the exploratory behavior of ants in finding the shortest path between their nest and food source. To increase the diversity in optimization and finding new solutions, a crossover operator based on pheromone is used. The defined performance index evaluates the optimization process. In this regard the finite element model is employed as an analytical tool in optimization process. The aim of optimizing continuous domain is to find the optimal design with minimum weight and maximum stiffness. To demonstrate the integrity and efficiency of the proposed method, numerical examples are presented and the results will be discussed.