Abstract: Dynamic knapsack problem (DKP) is a kind of classic dynamic optimization problems, which can be used to describe many practical issues. So far the study of dynamic knapsack problem has mainly focused on genetic algorithm,and particle swarm optimization algorithm is of rare application. This paper proposed a discrete particle swarm optimization algorithm based on discrete particle swarm optimization model for solving dynamic knapsack problem(DSDPSO)，and introduced environment change detection and post change response mechanism. Our algorithm was compared with the existing classical adaptive primal-dual genetic algorithm(API}GA) into two dynamic knapsack problems,and the resups show that the DSDPSO algorithm can rapidly find the optimal solution and remains stable after environment varialion. Consectuently, this algorithm is more suitable to solve dynamic knapsack problem.

Key words: Particle swarm optimization algorithm, Dynamic knapsack problem, DSDPSO algorithm, Set