A Hybrid Intelligent Algorithm for Product Optimization Configuration

Due to the combinatorial nature of product configuration problem and the characteristics of multi-objective and multi-constrain, an effective product configuration model is established to transform the complicated problem into the path optimization problem. A hybrid intelligent algorithm is adopted, which united the genetic principle, the ant colony mechanism and the simulation anneal theory into the original PSO algorithm. Based on the discrete characteristic of the product configuration problem, the hybrid intelligent algorithm is transformed from the sequential to the discrete. The significations of the position and the velocity are redefined, and the operation rules of these variables and the movement equations of the particles are determined. Finally, an example is given to evaluate the performance of the proposed approach. The simulation results validate the effectiveness of the proposed method in product configuration problem.