An Improved Quantum-behaved Particle Swarm Optimization Algorithm for the Knapsack Problem

An improved Quantum-behaved particle swarm optimization algorithm is proposed for 0-1 knapsack problem.In the new algorithm, the inertia weight is expressed as functions of particle evolution velocity and particle aggregation by defining particle evolution velocity and particle aggregation so that the inertia weight has adaptability. At the same time, slowly varying function is introduced to the traditional location updating formula so that the local optimal solution can be effectively overcome. The simulation experiments show that improved Quantum-behaved particle swarm optimization algorithm has better convergence and stability in solving knapsack problem.