BPSO Algorithms for Knapsack Problem

Particle Swarm Optimization (PSO) is an evolutionary metaheuristic. It was created in 1995 by Kennedy and Eberhart for solving optimization problems. However, several alternatives to the original PSO algorithm have been proposed in the literature to improve its performance for solving continuous or discrete problems. We propose in this paper 4 classes of binary PSO algorithms (BPSO) for solving the NP-hard knapsack problem. In the proposed algorithms, the velocities and positions of particles are updated according to different equations. To verify the performance of the proposed algorithms, we made a comparison between algorithms of the 4 proposed classes and a comparison between the proposed algorithms with the Standard PSO2006 and the Standard BPSO. The comparison results showed that the proposed algorithms outperform the Standard PSO2006 and the Standard BPSO in terms of quality of solution found.