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With the advent of the grid, task scheduling in heterogeneous environments becomes more and more important. The model of grid scheduling is analyzed in this paper. The optimal objective is to minimize the total completing time. This paper presents an improved particle swarm optimization (PSO) algorithm with discrete coding rule for grid scheduling problem. The improved PSO algorithm can keep all the advantages of the standard PSO, such as implementation simplicity, low computational burden, and few control parameters, etc. A set of experiments show that the algorithm is stable and presents low variability. The preliminary results obtained in this research are auspicious. We also tested the improved PSO algorithm against the MaxMin heuristic and found that improved PSO outperforms MaxMin by the total makespan and other performance.