Ant colony algorithm and simulated annealing algorithm based process route optimization

Process route sequencing is one of the key technologies for computer aided process planning (CAPP). In this paper, manufacturing feature was divided into several feature process elements and the precedence constraint matrix was generated by fully considering the constraint relationship among feature process elements. A hybrid algorithm, based on ant colony algorithm and simulated annealing algorithm, was proposed for process route sequencing. Considering the machine tools, cutting tools and fixtures as the manufacturing resources, minimal number of manufacturing resources changes served as the objective function to optimize the process route. The ant colony algorithm was adopted to traverse under the constraint rules among all the feature process elements, and simulated annealing algorithm was introduced to update pheromones to find the optimal process route meeting the constraint rules. To verify performance of the proposed approach, experimental studies have been conducted and comparisons have been made between this approach and some previous works. The experimental results show that the proposed approach has achieved significant improvement for process route sequencing.