Skip to Main Content
A discrete multi-objective particle swarm optimization (DMOPSO) algorithm is proposed in this paper. The algorithm adopts two different discretized strategies: directly rounding and redefining based on multi-objective particle swarm optimization with crowding distance (MOPSO_CD) and according to the characteristic of discrete variable. The crowding distance mechanism together with a mutation operator is used to maintain the external archive to add the diversity of Pareto optimal solutions, and the constraint handling mechanism is also adopted to handle constrained optimization problem. We applied the algorithm for the problem of grid workflow scheduling by a typical grid workflow instance. The experimental results indicate the feasibility and efficiency of the algorithm.